messy AI milestones

For me it is VERY useful to have a list of AI milestones with dates. This defines the ball park which is much, much bigger than ChatGPT. It provides a framework which helps inform future focus. The comments I've added are there as a self guide to future research. So, they often do hint at my favourites.

Keep in mind that there are at least four different types of AI: Symbolic, Neural Networks aka Connectionist, Traditional Robots and Behavioural Robotics, as well as hybrids. For some events in the timeline it is easy to map to the AI type but for others it is not so easy.

1943: Warren McCulloch, a neurophysiologist, and Walter Pitts, a logician, teamed up to develop a mathematical model of an artificial neuron. In their paper "A Logical Calculus of the Ideas Immanent in Nervous Activity" they declared that:

Because of the “all-or-none” character of nervous activity, neural events and the relations among them can be treated by means of propositional logic. It is found that the behavior of every net can be described in these terms.

1950: Alan Turing publishes “Computer Machinery and Intelligence” (‘The Imitation Game’ later known as the Turing Test)

1952: Arthur Samuel implemented a program that could play checkers against a human opponent

1954: Marvin Minsky submitted his Ph.D. thesis in Princeton in 1954, titled Theory of Neural-Analog Reinforcement Systems and its Application to the Brain-Model Problem; two years later Minsky had abandoned this approach and was a leader in the symbolic approach at Dartmouth.

1956: Dartmouth Workshop organised by John McCarthy coined the term Artificial Intelligence. He said would explore the hypothesis that "every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it."

The main descriptor for the favoured approach was Symbolist: based on logical reasoning with symbols. Later this approach was often referred to as GOFAI or Good Old Fashioned AI.

Knowledge can be represented by a set of rules, and computer programs can use logic to manipulate that knowledge. Leading symbolists Allen Newell and Herbert Simon argued that if a symbolic system had enough structured facts and premises, the aggregation would eventually produce broad intelligence.

Marvin Minsky, Allen Newell and Herb Simon, together with John McCarthy, set the research agenda for machine intelligence for the next 30 years. All were inspired by earlier work by Alan Turing, Claude Shannon and Norbert Weiner on tree search for playing chess. From this workshop, tree search — for game playing, for proving theorems, for reasoning, for perceptual processes such as vision and speech and for learning — became the dominant mode of thought.

1957: Connectionists: Frank Rosenblatt invents the perceptron, a system which paves the way for modern neural networks

The connectionists, inspired by biology, worked on "artificial neural networks" that would take in information and make sense of it themselves. The pioneering example was the perceptron, an experimental machine built by the Cornell psychologist Frank Rosenblatt with funding from the U.S. Navy. It had 400 light sensors that together acted as a retina, feeding information to about 1,000 "neurons" that did the processing and produced a single output. In 1958, a New York Times article quoted Rosenblatt as saying that "the machine would be the first device to think as the human brain."

Perceptrons were critiqued as very limited in what they could achieve by the symbolic advocates Minsky & Papert in their book Perceptrons. The Symbolists won this funding battle.

1959: John McCarthy noted the value of commonsense knowledge in his pioneering paper "Programs with Common Sense" [McCarthy1959]

1959:Arthur Samuel published a paper titled “Some Studies in Machine Learning Using the Game of Checkers”⁠2, the first time the phrase “Machine Learning” was used–earlier there had been models of learning machines, but this was a more general concept

1960: Frank Rosenblatt published results from his hardware Mark I Perceptron, a simple model of a single neuron, and tried to formalize what it was learning.

1960: Donald Michie himself built a machine that could learn to play the game of tic-tac-toe (Noughts and Crosses in British English) from 304 matchboxes, small rectangular boxes which were the containers for matches, and which had an outer cover and a sliding inner box to hold the matches. He put a label on one end of each of these sliding boxes, and carefully filled them with precise numbers of colored beads. With the help of a human operator, mindlessly following some simple rules, he had a machine that could not only play tic-tac-toe but could learn to get better at it.

He called his machine MENACE, for Matchbox Educable Noughts And Crosses Engine, and published⁠5 a report on it in 1961

1960s: Symbolic AI in the 1960s was able to successfully simulate the process of high-level reasoning, including logical deduction, algebra, geometry, spatial reasoning and means-ends analysis, all of them in precise English sentences, just like the ones humans used when they reasoned. Many observers, including philosophers, psychologists and the AI researchers themselves became convinced that they had captured the essential features of intelligence. This was not just hubris or speculation -- this was entailed by rationalism. If it was not true, then it brings into question a large part of the entire Western philosophical tradition.

Continental philosophy, which included Nietzsche, Husserl, Heidegger and others, rejected rationalism and argued that our high-level reasoning was limited, prone to error, and that most of our abilities come from our intuitions, our culture, and from our instinctive feel for the situation. Philosophers who were familiar with this tradition were the first to criticize GOFAI (Good Old Fashioned AI) and the assertion that it was sufficient for intelligence, such as Hubert Dreyfus and Haugeland.

1963: First PhD about computer vision by Larry Roberts MIT

1963: (1985) The philosopher John Haugeland in his 1985 book "Artificial Intelligence: The Very Idea" asked these two questions:

• Can GOFAI produce human level artificial intelligence in a machine?
• Is GOFAI the primary method that brains use to display intelligence?

AI founder Herbert A. Simon speculated in 1963 that the answers to both these questions was "yes". His evidence was the performance of programs he had co-written, such as Logic Theorist and the General Problem Solver, and his psychological research on human problem solving.

1966: Joseph Weizenbaum creates the Eliza Chatbot, an early example of natural language processing.

1967: MIT professor Marvin Minsky wrote: "Within a generation...the problem of creating 'artificial intelligence' will be substantially solved."

1968: Origin of Traditional Robotics: an approach to Artificial Intelligence by Donald Pieper, "The Kinematics of Manipulators Under Computer Control", at the Stanford Artificial Intelligence Laboratory (SAIL) in 1968.

1969-71: The classical AI "blocksworld" system SHRLDU, designed by Terry Winograd (mentor to Google founders Larry Page and Sergey Brin) revolved around an internal, updatable cognitive model of the world, that represented the software's understanding of the locations and properties of a set of stacked physical objects (Winograd,1971). SHRDLU carried on a simple dialog (via teletype) with a user, about a small world of objects (the BLOCKS world) shown on an early display screen (DEC-340 attached to a PDP-6 computer)

1979: Hans Moravec builds the Stanford Cart, one of the first autonomous vehicles (outdoor capable)

1980s: Back propagation and multi layer networks used in neural nets (only 2 or 3 layers)

1980s: Rule based Expert Systems, a more heuristic form of logical reasoning with symbols encoded the knowledge of a particular discipline, such as law or medicine

1984: Douglas Lenat (1950-2023) began work on a project he named Cyc that aimed to encode common sense in a machine. Lenat and his team added terms (facts and concepts) to Cyc's ontology and explained the relationships between them via rules. By 2017, the team had 1.5 million terms and 24.5 million rules. Yet Cyc is still nowhere near achieving general intelligence. Doug Lenat made the representation of common-sense knowledge in machine-interpretable form his life's work

Alan Kay's speech at Doug Lenat's memorial

1985: Robotics loop closing (Rodney Brooks, Raja Chatila) – if a robot sees a landmark a second time it can tighten up on uncertainties

1985: Origin of behavioural based robotics. Rodney Brooks wrote "A Robust Layered Control System for a Mobile Robot", in 1985, which appeared in a journal in 1986, when it was called the Subsumption Architecture. This later became the behavior-based approach to robotics and eventually through technical innovations by others morphed into behavior trees.

This has lead to more than 20 million robots in people’s homes, numerically more robots by far than any other robots ever built, and behavior trees are now underneath the hood of two thirds of the world’s video games, and many physical robots from UAVs to robots in factories.

1986: Marvin Minsky publishes "The Society of Mind". A mind grows out of an accumulation of mindless parts.

1986: David Rumelhart, Geoffrey Hinton, and Ronald Williams published a paper Learning Representations by Back-Propagating Errors, which re-established the neural networks field using a small number of layers of neuron models, each much like the Perceptron model. There was a great flurry of activity for the next decade until most researchers once again abandoned neural networks.

1986: Perhaps the most pivotal work in neural networks in the last 50 years was the multi-volume Parallel Distributed Processing (PDP) by David Rumelhart, James McClellan, and the PDP Research Group, released in 1986 by MIT Press. Chapter 1 lays out a similar hope to that shown by Rosenblatt:

People are smarter than today's computers because the brain employs a basic computational architecture that is more suited to deal with a central aspect of the natural information processing tasks that people are so good at. ...We will introduce a computational framework for modeling cognitive processes that seems… closer than other frameworks to the style of computation as it might be done by the brain.

Rumelhart and McClelland dismissed symbol-manipulation as a marginal phenomenon, “not of the essence human computation”.

1986: The term Deep Learning was introduced to the machine learning community by Rina Dechter in 1986

1987: Chris Langton instigated the notion of artificial life (Alife) at a workshop11 in Los Alamos, New Mexico, in 1987. The enterprise was to make living systems without the direct aid of biological structures. The work was inspired largely by John Von Neumann, and his early work on self-reproducing machines in cellular automata.

1988: One of Hinton's postdocs, Yann LeCun, went on to AT&T Bell Laboratories in 1988, where he and a postdoc named Yoshua Bengio used neural nets for optical character recognition; U.S. banks soon adopted the technique for processing checks. Hinton, LeCun, and Bengio eventually won the 2019 Turing Award and are sometimes called the godfathers of deep learning.

Late 1980s: The market for expert systems crashed because they required specialized hardware and couldn't compete with the cheaper desktop computers that were becoming common

1989: “Knowledge discovery in databases” started as an off-shoot of machine learning, with the first Knowledge Discovery and Data Mining workshop taking place at an AI conference in 1989 and helping to coin the term “data mining” in the process

1989: “Fast, Cheap, and Out of Control: A Robot Invasion of the Solar System”, by Rodney Brooks and Anita Flynn where we had proposed the idea of small rovers to explore planets, and explicitly Mars, rather than large ones that were under development at that time

1991: Rodney Brooks published “Intelligence without Reason”. This is both a critique of existing AI being determined by the current state of computers and a suggestion for a better way forward based on emulating insects (behavioural robotics)

1991: Simultaneous Localisation and Mapping (SLAM) Hugh Durrant-Whyte and John Leonard: symbolic systems replaced with geometry with statistical models of uncertainty ( used in self-driving cars , navigation and data collection from quadcopter drones, inputs from GPS )

1997: IBMs Deep Blue defeats world chess champion Gary Kasparov

1997: Soft landing of the Pathfinder mission to Mars. A little later in the afternoon, to hearty cheers, the Sojourner robot rover deployed onto the surface of Mars, the first mobile ambassador from Earth

Early 2000s: new symbolic-reasoning systems based on algorithms capable of solving a class of problems called 3SAT and with another advance called simultaneous localization and mapping. SLAM (Simultaneous Localisation and Mapping) is a technique for building maps incrementally as a robot moves around in the world

2001: Rodney Brooks company iRobot, on the morning of September 11, sent robots to ground zero in New York City. Those robots scoured nearby evacuated buildings for any injured survivors that might still be trapped inside.

2001-11: Packbot robots from irobot were deployed in the thousands in Afghanistan and Iraq searching for nuclear materials in radioactive environments, and dealing with road side bombs by the tens of thousands. By 2011 we had almost ten years of operational experience with thousands of robots in harsh war time conditions with human in the loop giving supervisory commands

2002: iRobot (Rodney Brooks company) introduced the Roomba

2005: The DARPA (Defense Advanced Research Projects Agency) Grand Challenge was won by Stanford Driverless car by driving 211 km on an unrehearsed road

2006: Geoffrey Hinton and Ruslan Salakhutdinov, published "Reducing the Dimensionality of Data with Neural Networks", where an idea called clamping allowed the layers to be trained incrementally. This made neural networks undead once again, and in the last handful of years this deep learning approach has exploded into practicality of machine learning

2009: Foundational work on neurosymbolic models is (D’AvilaGarcez,Lamb,& Gabbay,2009) which examined the mappings between symbolic systems and neural networks

2010s: Neural nets learning from massive data sets

2011: A week after the tsunami, on March 18th 2011, when Brooks was still on the board of iRobot, we got word that perhaps our robots could be helpful at Fukushima. We rushed six robots to Japan, donating them, and not worrying about ever getting reimbursed–we knew the robots were on a one way trip. Once they were sent into the reactor buildings they would be too contaminated to ever come back to us. We sent people from iRobot to train TEPCO staff on how to use the robots, and they were soon deployed even before the reactors had all been shut down.

The four smaller robots that iRobot sent, the Packbot 510, weighing 18kg (40 pounds) each with a long arm, were able to open access doors, enter, and send back images. Sometimes they needed to work in pairs so that the one furtherest away from the human operators could send back signals via an intermediate robot acting as a wifi relay. The robots were able to send images of analog dials so that the operators could read pressures in certain systems, they were able to send images of pipes to show which ones were still intact, and they were able to send back radiation levels. Satoshi Tadokoro, who sent in some of his robots later in the year to climb over steep rubble piles and up steep stairs that Packbot could not negotiate, said⁠3 “[I]f they did not have Packbot, the cool shutdown of the plant would have [been] delayed considerably”. The two bigger brothers, both were the 710 model, weighing 157kg (346 pounds) with a lifting capacity of 100kg (220 pounds) where used to operate an industrial vacuum cleaner, move debris, and cut through fences so that other specialized robots could access particular work sites.

But the robots we sent to Fukushima were not just remote control machines. They had an Artificial Intelligence (AI) based operating system, known as Aware 2.0, that allowed the robots to build maps, plan optimal paths, right themselves should they tumble down a slope, and to retrace their path when they lost contact with their human operators. This does not sound much like sexy advanced AI, and indeed it is not so advanced compared to what clever videos from corporate research labs appear to show, or painstakingly crafted edge-of-just-possible demonstrations from academic research labs are able to do when things all work as planned. But simple and un-sexy is the nature of the sort of AI we can currently put on robots in real, messy, operational environments.

2011: IBM’s Watson wins Jeopardy

2011-15: Partially in response to the Fukushima disaster the US Defense Advanced Research Projects Agency (DARPA) set up a challenge competition for robots to operate in disaster areas

The competition ran from late 2011 to June 5th and 6th of 2015 when the final competition was held. The robots were semi-autonomous with communications from human operators over a deliberately unreliable and degraded communications link. This short video focuses on the second place team but also shows some of the other teams, and gives a good overview of the state of the art in 2015. For a selection of greatest failures at the competition see this link.

2012: Nvidia noticed the trend and created CUDA, a platform that enabled researchers to use GPUs for general-purpose processing. Among these researchers was a Ph.D. student in Hinton's lab named Alex Krizhevsky, who used CUDA to write the code for a neural network that blew everyone away in ImageNet competition, which challenged AI researchers to build computer-vision systems that could sort more than 1 million images into 1,000 categories of objects

AlexNet's error rate was 15 percent, compared with the 26 percent error rate of the second-best entry. The neural net owed its runaway victory to GPU power and a "deep" structure of multiple layers containing 650,000 neurons in all.

In the next year's ImageNet competition, almost everyone used neural networks.

2013-18: Speech transliteration systems improve and proliferate – we can talk to our devices

2014: Google program had automatically generated this caption: “A group of young people playing a game of Frisbee”. (reported in a NYT article)

2015: LeCun, Bengio, Hinton (LeCun 2015)
Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Deep learning discovers intricate structure in large data sets by using the backpropagation algorithm to indicate how a machine should change its internal parameters that are used to compute the representation in each layer from the representation in the previous layer. Deep convolutional nets have brought about breakthroughs in processing images, video, speech and audio, whereas recurrent nets have shone light on sequential data such as text and speech.

2015: Diffusion models were introduced in 2015 as a method to learn a model that can sample from a highly complex probability distribution. They used techniques from non-equilibrium thermodynamics, especially diffusion. Diffusion models have been commonly used to generate images from text. Still, recent innovations have expanded their use in deep-learning and generative AI for applications like developing drugs, using natural language processing to create more complex images and predicting human choices based on eye tracking.

2016: Google's AlphaGo AI defeated world champion Lee Sedol, with the final score being 4:1.

2017: In one of Deep Mind’s most influential papers “Mastering the game of Go without human knowledge”,the very goal was to dispense with human knowledge altogether, so as to “learn, tabularasa, superhuman proficiency in challenging domains”(Silveretal.,2017).
(this claim has been disputed by Gary Marcus)

2017-19: New architectures, such as the Transformer(Vaswanietal.,2017) developed, which underlies GPT-2(Radfordetal.,2019)

2018: Behavioural AI:
Blind cheetah robot climbs stairs with obstacles: visit the link then scroll down for the video

2019: Hinton, LeCun, and Bengio won the 2019 Turing Award and are sometimes called the godfathers of deep learning.

2019: The Bitter Lesson by Rich Sutton, one of founders of reinforcement learning.

The biggest lesson that can be read from 70 years of AI research is that general methods thatleverage computation are ultimately the most effective, and by a large margin…researchers seek to leverage their human knowledge of the domain, but the only thing that matters in the long run is the leveraging of computation.…the human-knowledge approach tends to complicate methods in ways that make them less suited to taking advantage of general methods leveraging computation.

(This analysis is disputed by Gary Marcus in his hybrid essay)

2019: Rubik’s cube solved with a robot hand: video

2020: Open AI introduces GPT3 natural language model which later spouts bigoted remarks

2021: DALL-E images from text captions

2022: Text to images
Stable Diffusion is a deep learning, text-to-image model released in 2022 based on diffusion techniques. It is considered to be a part of the ongoing artificial intelligence boom. It is primarily used to generate detailed images conditioned on text descriptions.

Stable Diffusion is a latent diffusion model, a kind of deep generative artificial neural network. Its code and model weights have been released publicly, and it can run on most consumer hardware equipped with a modest GPU with at least 4 GB VRAM. This marked a departure from previous proprietary text-to-image models such as DALL-E and Midjourney which were accessible only via cloud services.

2022, November: ChatGPT is a chatbot and virtual assistant developed by OpenAI and launched on November 30, 2022. Based on large language models (LLMs), it enables users to refine and steer a conversation towards a desired length, format, style, level of detail, and language. Successive user prompts and replies are considered at each conversation stage as context.

ChatGPT is credited with starting the AI boom, which has led to ongoing rapid investment in and public attention to the field of artificial intelligence (AI). By January 2023, it had become what was then the fastest-growing consumer software application in history, gaining over 100 million users and contributing to the growth of OpenAI's current valuation of $86 billion.

Frontier Justice by Tony Roberts

I remember being impressed by the meticulous research in this book when I read it in 2018. IMO it is essential reading for those who want to understand the frontier wars. Keith Windschuttle has challenged this sort of information when it has been put forward by other authors, such as Henry Reynolds, in what is known as the history wars: the true impact of British colonialism on Australian aboriginals and Torres Strait Islanders. I did look for critical reviews of this book but couldn't find any.

I found a review I agreed with (here) and am quoting it in full.

Frontier Justice: A History of the Gulf Country to 1900 by Tony Roberts (2005)

Tony Roberts begins his monumental study of Aboriginal-white frontier relations by describing the harshness, remoteness and dangers of the Gulf country, a vast region stretching from the Barkley Tablelands to the Roper River in the Northern Territory and from the Stuart Highway to the Queensland border and beyond as far as Burketown. The region is centred on the isolated township of Borroloola.

As Roberts notes, this was Australia’s last frontier. Even today the area is remote and little known to most Australians. The strength of Robert’s study of frontier relations in this region is evident from the start in the deft and telling way he sets the context. During the pastoral boom of the 1880s thousands of head of cattle were driven along the ‘coast track’ from Queensland to Roper Bar and Katherine in the Northern Territory to stock the vast stations being established. There followed many hopeful individuals seeking riches in the Kimberley gold rush. Roberts notes this was ‘a momentous time in Australian history’.

However, describing the enormity of the dispossession and destruction that overwhelmed the tribes of the area in the short space of two decades, Roberts applies those same words to describe the significance of these events for Aboriginal society. He says it was ‘a momentous time in Aboriginal history’. The implication is clear – there are two histories in this country. Roberts sets himself the task of exploring both versions, and in the process throws much light on previously hidden aspects of the interaction of the two societies, settler and Aboriginal, in this remote frontier region.

Roberts’ detailed, almost forensic, examination of this relationship reveals a tragic and cruel tale. The damage inflicted, sometimes unwittingly, but all too often with callous intent, on the Aboriginal people of the region, is captured in the words of his title – ‘frontier justice’ – a title redolent with irony, as the reader becomes only too well aware as the story of the destruction wrought upon Aboriginal society is revealed.

Frontier Justice provides a detailed account of the history of the area to 1900 on a chronological and on an area by area basis. Although this approach leads to some repetition, the result is a comprehensive account. Roberts has spent 30 years researching and writing this book. It is a labour of both love and despair. The story Roberts tells is one of rape, abduction and murder of Aboriginal people by brutal whites (and Roberts makes abundantly clear that not all whites were brutal), of Aboriginal reprisals by way of killing of whites (Roberts uses the term ‘murder’), spearing of stock and setting fire to the country. The deadly cycle of reprisal, including ‘punitive expeditions’, then comes into play. Indiscriminate shooting of Aboriginal men, and sometimes of women and children, became the method of ‘controlling the blacks’. Roberts builds a strong case to show that the police were active agents in the punitive expeditions, and in particular raises serious concerns about the role played by Inspector Paul Foelsche who was in charge of policing in the northern half of the Territory from 1870 to 1904.

Roberts explains that essential to the subjugation of the Aboriginal tribes was the conspiracy of silence that prevailed. This kept the metropolitan government in Adelaide at bay as they struggled ineffectively to keep some control of the Northern Territory situation. One needed to know the code to understand what was happening – Aboriginal people were not ‘shot’, they were ‘dispersed’. When reports were written they understated the numbers killed and misrepresented the circumstances. Bushmen were not obliged to join in the hunting of Aborigines, but they were required to keep silent about what they knew. Roberts has managed to penetrate this ‘veil of secrecy’ only through an enormous research effort. He has uncovered many key documents from archives and personal possessions which have not previously seen the light of day. He has relied on a wide variety of sources, published and unpublished, including extensive Aboriginal oral history. It is a cover-up that almost succeeded.

Such a mass of information could have been overwhelming, and made such an account as this turgid and difficult. However, Roberts writes with an economy of words that repay close attention as they carry much information, directly and by implication. Writing of the punitive expeditions, Roberts notes: ‘In the fledgling Northern Territory they [the punitive expeditions] were commonplace: supported by government officials, applauded by the local press, perpetrated by ordinary men and sometimes led by senior police officials’.[1] The sentence says a lot about the nature of the Australian frontier. Roberts’ book is lengthy not because the author is wordy, but because of the mass of information it contains.

As well as punitive expeditions, casual shootings and assorted violence, Roberts describes the forced sexual mistreatment of women and children in the region. Venereal disease became rampant and was untreated. The practice of kidnapping young children left old people to fend for themselves – often destitute and starving.

However, a parade of violence, well-researched and documented as it is, would not take us far in understanding the dynamics of the frontier. Roberts shows that lying behind the self-justified and largely unchecked violence was the assumption that the Aboriginal people had no rights in the lands they had occupied for millennia. On the other hand, the whites had, apparently, the right to travel through, or even take possession of, these lands. Any opposition on the part of the Aboriginal people was seen as contrariness, treachery or criminality. This is the true psychology of terra nullius. Roberts himself pinpoints this assumption by the whites: ‘The land was simply occupied as if it were terra nullius and severe punishment was meted out to any Aboriginal who resisted’.[2]

Frontier Justice is a well-informed, closely researched and absorbing book. It is a work of detailed scholarship which manages to be objective, in the sense of a dispassionate search after historical truth, and morally engaged at the same time. Roberts does not hesitate to name moral bankruptcy. Frontier Justice strips away the romanticised view of the pioneering days which has largely served to hide the brutal and difficult realities of our past. These realities have to be faced. Frontier Justice makes a significant contribution to this task. It deserves to be in every school, university and public library.

Australia's shameful history

“This history is so shameful that most Australians could not admit that this is the origin of their state and their nation”
— Indigenous historian Marcia Langton, in The First Australians.

When I grew up in Melbourne in the 1950s the history of what happened to the aboriginals was invisible. No one talked about it. As Bill Stanner said in 1968 it was the great Australian silence, a cult of forgetfulness on a national scale. A view from the window where a significant part of the landscape was hidden.

Some of my marxist comrades say something like this:
Aboriginal resistance to colonialism can’t be supported because their social system was too backward, primitive, “stone age”. Further, it is argued that Marx supported globalisation and implied from that, that he supported colonialism. See Marx Supported Capitalist Globalization  According to this dialectic the British occupation of Australia was basically a good thing. Modernity is good, superior to any form of pre-modern society. Perhaps I am not portraying their position correctly. They can fix that.

What I am thinking:
This mindset filters out some uncomfortable facts. We see the world through our mind memes, the state of our mind determines what we choose to see. Hence, some of these comrades end up say that Windschuttle was correct in his denial of massacres. I've been told that historians such as Lyndall Ryan and Henry Reynolds either exaggerated or lied and never admitted it when they were caught out. I can except that but believe that their fundamental position is correct, that widespread, systematic massacres occurred.

What facts?
That there were repeated massacres of aboriginal people. Following from the terra nullius doctrine aboriginal people were not treated as having any rights. So, in Tasmania the ex convict settlers took their women. In Queensland pastoralists took their land, etc, etc. Any thinking person should be able to see that this would inevitably lead to conflict. I filter the facts through that context, terra nullius and what would have to flow from that. Aboriginal people responded by killing whites or cattle. In response the whites responded by multiple killings of aboriginals, the only viable way in the conditions of the early colonies, to “teach them a lesson”. Those doing the massacres were usually not brought to justice. Either a blind eye was turned or the massacres were kept secret from authorities.

The evidence:
I didn’t always know this as mentioned earlier. When I went to Far North Queensland (Pauline Hansen country) I learnt through reading (eg. Henry Reynolds) and talking to people that the mindset of “keeping the abos in their place” was widespread. A cleaner at Djarragun College told me that during a holiday further north a publican had told her that when driving home at night if an aboriginal was on the road the best thing to do was run them over.

At any rate, I’ve read these books which I believe provide adequate documentation of both the mindset and the facts:
All that is solid melts into air by Marshall Berman
The Politics of Suffering by Peter Sutton
The Tall Man by Chloe Hooper
* The Black War by Nicholas Clements
* Why Warriors Lie Down and Die by Richard Trudgen
* Why weren’t we told? by Henry Reynolds
* Forgotten War by Henry Reynolds
* Frontier Justice by Tony Roberts
Disciplining the Savages, Savaging the Disciplines by Martin Nakata
Cosmopolitanism by Kwame Anthony Appiah
Colonial Frontier Massacres, Map (Date Range: 1780 to 1930)
Colonial Frontier Massacres, Timeline
Colonial Frontier Massacres, Preliminary Findings
* Dancing with Strangers by Inga Clendinnen
* The Sinister Glamour of Modernity by Ross Gibson
Australian Frontier Wars: Keith Windschuttle and Henry Reynolds on Lateline (2001, 22 minutes)
Australian Frontier Wars: Keith Windschuttle and Henry Reynolds at the National Press Club (2001, 58 minutes)
* Man from Arltunga: Walter Smith Australian Bushman by Dick Kimber
Gillen's Modest Record edited by Philip Jones
Boyer Lectures 2019, by Rachel Perkins (audio)
debate between Robert Manne and Keith Windschuttle at the Melbourne Writers Festival, part one, part 2  (September, 2003)

Of these, perhaps the best documented books about the massacres (rather than the mindset) are those by Clements (about Tasmania) and Roberts (about Queensland and the NT). I mention this because I accept that everyone is busy on their own projects and doesn't have time to read everything.

I've put a * next to the books which provide evidence that it was standard practice from 1790 - 1930 to kill aboriginal and TSI that settlers had a problem with

Update (Jan 19): Added some more books and links. In particular the debate between Keith Windschuttle and Henry Reynolds at the National Press Club (58 minutes) is worth watching.

"justice" 1870's-1930's

The late Paddy Tucker independently stated that he believed Willoberta Jack to have been poisoned. As he explained, from the 1870's-1930's no Aboriginal or person of Aboriginal descent could expect to escape if he or she killed a white person, even though the killing might be in self defence. There were always some white people who would ensure that the Aboriginal person was killed in the name of "justice" and "keeping the niggers in line".
Footnote 5, p. 124 Man from Arltunga: Walter Smith Australian Bushman by RG Kimber

Background information: Willoberta killed Harry Henty in the late 1920s after Henty attempted to shoot Willoberta because Willoberta refused to allow Henty to rape his underage daughter. Willoberta went into hiding for years and when he emerged was found not guilty by reason of self defence. But later on a fella by the name of Jimmy Donu gave Willoberta a bag of flour in which poison was chucked in before the flour was put in.

why software might be superior knowledge

Software is not a product. It is a medium in which we store knowledge. Historically, in the order of their coming about, there have been 5 such media:

1. DNA
2. Brains
3. Hardware
4. Books
5. Software

The reason software has become the storage medium of choice is that knowledge in software has been made active. It has escaped the confinement and volatility of knowledge in brains; it avoids the passivity of knowledge in books; it has the flexibility and speed of change missing from knowledge in DNA or hardware.

This analysis originates from Philip Armour. The five orders of ignorance.

The Origins of Modernity

Giordano Bruno (1548-1600, burnt alive by the Church) and Francis Bacon (1561-1626) put forward a clear program of domination or conquest of nature around about 1583-85, the time that Bruno visited England.

“The gods have given man intelligence and hands, and have made them in their image, endowing him with a capacity superior to other animals. This capacity consists not only in the power to work in accordance with nature and the usual course of things, but beyond that and outside her laws, to the end that by fashioning, or the power to fashion, other natures, other courses, other orders by means of his intelligence, with that freedom without which his resemblance to the deity would not exist, he might in the end make himself god of the earth … providence has decreed that man should be occupied in action by the hands and in contemplation by the intellect, but in such a way that he may not contemplate without action or work without contemplation …. when difficulties beset them or necessities reappeared … they sharpened their wits, invented industries and discovered arts … by force of necessity, from the depths of the human mind rose new and wonderful inventions.”
- Bruno, The Expulsion of the Triumphant Beast

Albert Schweitzer points out that an optimistic view of a modern world where knowledge, standard of living and health could all be improved (as compared with passive acceptance of ignorance, poverty and ill health) met considerable opposition from historical forces. Plato's ethic is world negation., Plato and Aristotle accepted slavery and so did not envisage the liberation of Humanity as a whole. The Epicureans and Stoics preached resignation.

Bacon took the moral stance that real charity involved meeting peoples needs in the full Christian sense of brotherly love. He contrasted this with the tendency of the Greeks to quarrel about opinions.

After dabbling in politics, initially without much success, Bacon took the view that invention was more useful than politics because it is felt everywhere and lasts forever.

Invention required the use of both intellect and labour, the head and the hand. The “mechanical arts” became central to Bacon's vision, he wanted the concepts spread far and wide to a thousand hands and a thousand eyes.

Bacon persistently criticised the influence of Aristotle and Plato on contemporary thinking because their mode of thinking (dialectical argument) did not support the rapid development of the mechanical arts.

Reference:
The Philosophy of Francis Bacon by Benjamin Farrington (1964), Ch 4, 5 and 6

philosophers timeline

FIRST ENLIGHTENMENT

Thales 625 BC - ?
Anaximander 610 BC - ?
Pythagoras 560 BC - ?
Heraclitus 535 BC-475 BC
Zeno of Elea 490-430 BC
Democritus 460 BC-?
Socrates 469-399 BC
Euclid ? - 366 BC
Plato 429-347 BC
Aristotle 384 BC-322 BC
Epicurus 341-271 BC
Archimedes 287 – 212 BC
Chrysippus 280-206 BC
Cicero 106-43 BC
Ovid 43 BC-17 AD
Seneca 1-65
Plutarch 45-120
Lucretius early to mid 1st C

NOT MUCH PROGRESS YEARS

Thomas Aquinas 1225-1274
William of Occam 1285-1347

SECOND ENLIGHTENMENT

Nicolaus Copernicus 1473-1543
Michel de Montaigne 1533-1592
Giordano Bruno 1548-1600 (burnt alive by the Church)
Francis Bacon 1561-1626
Galileo Galilei 1564-1642
Johannes Kepler 1571-1630
Thomas Hobbes 1588-1679
Rene Descarte 1596-1650
Gerrard Winstanley 1609-1676
Blaise Pascal 1623-1662
Robert Boyle 1627-1691
Christiaan Huygens 1629-1695
Baruch Spinoza 1632-1677
John Locke 1632-1704
Robert Hooke 1635-1703

ENGLISH REVOLUTION / CIVIL WAR 1642-1660

Isaac Newton 1642-1727
Gottfried Wilhelm Liebniz 1646-1716
Jonathan Swift 1667-1745
Christian Wolff 1679-1754
George Berkeley 1685-1753
Montesquieu 1689-1755
Voltaire 1694-1778
Carl Linnaeus 1701-1778
Thomas Bayes 1702-1761
David Hume 1711-1776
John Jacques Rousseau 1712-1778
Étienne Bonnot de Condillac 1714-1780
Claude Adrien Helvetius 1715-1771
Baron d'Holbach 1723-1789
Adam Smith 1723-1790
Immanuel Kant 1724-1804
Georg Lichtenberg 1742-1799
Nicolas de Condorcet 1743-1794
Johann Gottfried Herder 1744-1803
Jeremy Bentham 1748-1832
Pierre-Simon Laplace 1749-1827
Johann Wolfgang von Goethe 1749-1832
Joseph de Maistre 1753-1821
Henri de Saint-Simon 1760-1825
Johann Gottlieb Fichte 1762-1814
Pierre Maine de Biran 1766-1824
Georg Wilhelm Friedrich Hegel 1770-1831
Charles Fourier 1772-1837

FRENCH REVOLUTION 1787-1799

Arthur Schopenhauer 1788-1860
Richard Jones 1790-1855
Charles Babbage 1791-1871
John Herschel 1792-1871
William Whewell 1794-1866
Auguste Comte 1798-1857
John Stuart Mill 1806-73
Charles Darwin 1809-1882
Soren Kiekegaard 1813-1855
Karl Marx 1818-1883
Friedrich Engels 1820-1895
Ernst Mach 1838-1916
Charles Peirce 1839-1914
William James 1842-1910
Frederick Nietzsche 1844-1900
Georg Cantor 1845-1918
Gottlob Frege 1848-1925
Henri Poincaré 1854-1912
Emile Durkheim 1858-1917
Giuseppe Peano 1858-1932
Edmund Husserl 1859-1938
Henri Bergson 1859-1941
John Dewey 1859-1952
Rabindranath Tagore 1861-1941
Alfred North Whitehead 1861-1947
George Herbert Mead 1863-1931
Vladimir Lenin 1870-1924
Arthur Bentley 1870 - 1957
Marcel Proust 1871-1922
Bertrand Russell 1872-1970
GE Moore 1873-1958
Albert Einstein 1879-1955
Moritz Schlick 1882-1936
Otto Neurath 1882-1945
Aldous Huxley 1894-1963
Ludwig Wittgenstein 1889-1951
Martin Heidegger 1889-1976
Hans Reichenbach 1891-1953
Rudolf Carnap 1891-1970
Mao Zedong 1893-1976
Mikhail Bakhtin 1895 -1975
Lev Vygotsky 1896-1934
Gilbert Ryle 1900-1976
Aron Gurwitsch 1901-1973
Herbert Feigl 1902-1988
Karl Popper 1902-1994
Georges Politzer 1903-1942
George Orwell 1903-1950
Alexei Leontiev 1903-1979
Gregory Bateson 1904-1980
BF Skinner 1904-1990
Jean-Paul Sartre 1905-1980
Raymond Aron 1905-1983
Carl Gustav Hempel 1905-1997
Kurt Godel 1906-1978
Emmanuel Levinas 1906-1995
Nelson Goodman 1906-1998
Maurice Merleau-Ponty 1908-1961
Willard Van Ormon Quine 1908-2000
Isaiah Berlin 1909-1997
A. J. Ayer 1910-1989
John Langshaw Austin 1911-1960
Alan Turing 1912-1954
Wilfrid Sellers 1912-1989
Paul Ricoeur 1913-2005
Harold Garfinkel 1917-2011
Iris Murdoch 1919-1999
Elizabeth Anscombe 1919-2001
John Rawls 1921-2002
Imre Lakatos 1922-1974
Thomas Kuhn 1922-1996
Michel Henry 1922–2002
Evald Ilyenkov 1924-1979
Paul Feyerabend 1924-1994
Gilles Deleuze 1925-1995
Michel Foucault 1926-1984
Hilary Putnam 1926-2016
Klaus Holzkamp 1927-1995
Marvin Minsky 1927-2016
Seymour Papert 1928-2016
Bernard Williams 1929-2003
Merab Mamardashvili 1930-1990
Allan Bloom 1930-1992
Pierre Bourdieu 1930-2002
Jacques Derrida 1930-2004
Felix Mikhailov 1930-2006
Richard Rorty 1931-2007
Vladimir Bibikhim 1938-2004
Myles Burnyeat 1939-2019
Marshall Berman 1940-2013
Francisco Varela 1946-2001

STILL ALIVE

Noam Chomsky 1928-
Humberto Maturana 1929-
Maxine Sheets-Johnstone 1930-
Amartya Sen 1933-
Jerry Fodor 1935-
Ian Hacking 1936 -
Michael J Crowe 1936 -
Helene Cixous 1937-
Ronald Giere 1938 -
Mike Cole 1938-
Jean-Luc Nancy 1940-
Bas van Fraasen 1941-
Larry Laudan 1941-
Paul Churchland 1942-
Daniel Dennett 1942-
Marcello Pera 1943-
Donald Gillies 1944 -
Douglas Hofstadter 1945-
Hartry Field 1946 -
Martha Nussbaum 1947-
Camille Paglia 1947-
Bruno Latour 1947-
Richard Yeo 1948-
Yrjo Engestrom 1948 -
Andrew Pickering 1948-
David Weinberger 1950-
Rebecca Goldstein 1950-
Luc Ferry 1951-
Wolff-Michael Roth 1953-
Kwame Anthony Appiah 1954-
Paul Boghossian 1957 -
Andy Clark 1957-
Michele Moody-Adams 1956-
Laura Snyder 1964-
Vanessa Wills ? -
Lucy Suchman ? -

I have been adding to this from time to time.

the black memory hole

Henry Reynolds has estimated that aborigines killed somewhere between 2000 and 2500 Europeans in the course of the European invasion and settlement of Australia.

He further estimated that at least 20,000 aborigines were killed as a direct result of conflict with the settlers. If anything, the latter estimate errs on the side of caution.

Henry Reynolds claims that he was the first person who tried to quantify the aboriginal death toll. His estimates were first published in The Other Side of the Frontier in 1981 (amazon, review by Humphrey McQueen)

Why are we never told these figures? Why isn't it part of the school curriculum? Our memory of these events has disappeared down a black hole.

Many Australians don't want to look at the dark side of our history. A veil is drawn.

But if these bodies had been white then our history would be full of their story, monuments would be everywhere to celebrate their sacrifice. As we do on Anzac Day.

Henry Reynolds goes onto to document figures that reveal that in the north of Australia twice as many blacks were killed in a 70 year period (1861 to 1930s) as whites (Europeans) were killed in the five wars between the Boer War and Vietnam war, a different 70 year period.

Don't these figures reveal that the black wars were the most significant in Australian history?

Reference: Why Weren't We Told? by Henry Reynolds (1999), pp. 113-116

books I've been reading in 2016

This turns out to be a mixture of indigenous issues, philosophical thinking, Australian history, science, maths instruction and other oddities.

Bennett, Ronan. Zugzwang (2007)
Blanchard, Ken. The One Minute Manager Meets the Monkey (1990)
Brooks, Geraldine. Year of Wonders: A Novel of the Plague (2001)
Canada, Geoffrey. Fist, Stick, Knife, Gun: A Personal History of Violence (1995)
Cohen-Solal. Sartre: A Life (2005)
Dawes, Glenn; Northfield, Peter; Wallace, Ken. Astronomy 2016 Australia: Your Guide to the Night Sky (2015)
Dixon, Robert. Words of our Country: Yidiny – The Aboriginal Language of the Cairns – Yarrabah Region (2015)
Farkota, Rhonda. Elementary Maths Mastery (2000)
FitzSimons Peter. Batavia (2011)
Gaita, Raimond. Romulus, My Father (1998)
Gaita, Raimond. The Philosopher's Dog: Friendships with Animals (2002)
Goodwin, Doris Kearns. Team of Rivals: The Political Genius of Abraham Lincoln (2005)
Hooper, Chloe. The Tall Man: Death and Life on Palm Island (2009)
Hooper, Judith. Of Moths and Men: Intrigue, Tragedy and the Peppered Moth (2002)
Jarrett, Stephanie. Liberating Aboriginal People from Violence (2013)
Jordan, Mary Ellen. Balanda: My Year in Arnhem Land (2005)
Kehlmann, Daniel. Measuring the World (2007)
Langton, Marcia. Well, I Heard It on the Radio and I Saw It on the Television… (1993)
Le Guin, Ursula. The Lathe of Heaven (1971)
McIntosh, Dennis. The Tunnel (2014)
McIntosh, Dennis. Volume One, Creative Work: Tunnelling (PhD thesis, 2013)
Michaels, Walter Benn. The Trouble with Diversity: How we Learned to Love Identity and Ignore Inequality (2006)
Mighton, John. Nurturing Mathematical Talent in Every Child (2003)
Monteath, Peter and Munt, Valerie. Red Professor: The Cold War Life of Fred Rose (2015)
Nakata, Martin. Disciplining the Savages, Savaging the Disciplines (2007)
Nussbaum, Martha. Upheavals of Thought: The Intelligence of Emotions (2001)
Osborne, Barry, and Osborne, Elizabeth (2013) A Serious Dialogue with Noel Pearson's Radical Hope: education and equality in Australia.
Pascoe, Bruce. Dark Emu Black Seeds: Agriculture or Accident? (2014)
Pearson, Noel. Radical Hope: Education and Equality in Australia (2012). Get the version which has replies to the author and the authors replies to those replies, better than the original Quarterly Essay version.
Petraitis, Vicky. The Dog Squad (2015)
Porter, Liz. Written on the Skin: An Australian Forensic Casebook (2007)
Porter, Liz. Unnatural Order (1995)
Reynolds, Henry. Why Weren't We Told? (1999)
Reynolds, Henry. North of Capricorn: The Untold Story of the People of Australia's North (2003)
Sutton, Peter. The Politics of Suffering: Indigenous Australia and the end of the liberal consensus (2009)
Trudgen, Richard. Why Warriors Lie Down and Die (2000)
Yunkaporta, Tyson. Aboriginal Pedagogies at the Cultural Interface (2009)

Some books I read in 2015

I've been too busy to blog because of my new job. However, after 6 months, the pressure is beginning to lift a little and so I might be able to manage a blog or two.

I want to list the books I read (or reread) last year (2015) since good books play such an important part in my life and consciousness. This acts as a reminder of some of the places my mind has visited not so long ago, as a wandering wonderer.

NON FICTION
Berlin, Isiah. Freedom and its Betrayal: Six Enemies of Human Liberty (2002)
Berlin, Isiah. The Roots of Romanticism (1999)
Berman, Marshall. Everything Solid Melts into Air: The Experience of Modernity (1982)
Berman, Marshall. The Politics of Authenticity: Radical Individualism and the Emergence of Modern Society (1970)
Dennett, Daniel. Consciousness Explained (1991)
Eagleton, Terry. Why Marx was Right (2011)
Greenwald, Glen. No Place to Hide: Edward Snowden, the NSA and the US Surveillance State (2015)
Harris, Sam. Free Will (2012)
Hill, Christopher. The World Turned Upside Down: Radical Ideas During the English Revolution (1972)
Kahneman, Daniel. Thinking, Fast and Slow (2011)
Hofstadter, Douglas. I am a Strange Loop (2007)
Murdoch, Iris. Existentialists and Mystics: Writings on Philosophy and Literature (1997)
Murray, Patrick. Marx's Theory of Scientific Knowledge (1998)
Ollman, Bertell. Alienation: Marx's Conception of Man in Capitalist Society (1971)
Ollman, Bertell. Dance of the Dialectic: Steps in Marx's Method (2003)
Putnam, Hilary. Philosophy in an Age of Science: Physics, Mathematics and Skepticism (2012)
Strong, Anna Louise. The Stalin Era (1957)
Wills, Vanessa. Marx and Morality (2011)
Yalom, Irvin. Love’s Executioner (1968)

FICTION
Hamid, Mohsin. The Reluctant Fundamentalist (2007)
Le Guin, Ursula. The Dispossessed. (1974)
Sobel, Dava. Longitude: The True Story of a Lone Genius Who Solved the Greatest Scientific Problem of His Time (1995)
Sobel, Dava. A More Perfect Heaven: How Copernicus Revolutionized the Cosmos (2011)
Sobel, Dava. Galileo's Daughter: A Historical Memoir of Science, Faith, and Love (1999)
Yalom, Irvin. The Schopenhauer Cure (2005)
Yalom, Irvin. The Spinoza Problem (2012)

What Marx said about the individual in "The German Ideology"

I've been discussing, mainly with Peter, and thinking about the concept of the individual. What is an individual? One avenue has been to clarify what Marx said about this. What follows is a summary of part of his writings. There will be other posts about Marx and other authors to follow, on this topic.

The German Ideology was written in 1845-6, when Marx was 27 or 28 yo. I mention this because some argue there are significant differences between the young Marx and the older Marx.

Part of the Feuerbach section of The German Ideology
D. PROLETARIANS AND COMMUNISM
Individuals, Class and Community

Here is my summary:

The context is a discussion of the rise of the trading or mercantile class (burghers) in antagonism to the feudal class. Over time the trading class develops into the bourgeoisie or propertied class. Traders and bourgeois compete intensely with each other but are also compelled to unite with each other in their struggle to overthrow the feudal class.

Marx says clearly that individuals arise historically before classes. In footnote 2 Marx specifically rejects the formulations that "each is all", "that bourgeois is only a specimen of the bourgeois species" and "that the class of bourgeois existed before the individuals constituting it".

Individuals act as individuals, including competing with each other, but as classes develop they discover they are members of a class.

"The separate individuals form a class only insofar as they have to carry on a common battle against another class; otherwise they are on hostile terms with each other as competitors. On the other hand, the class in its turn achieves an independent existence over against the individuals, so that the latter find their conditions of existence predestined, and hence have their position in life and their personal development assigned to them by their class, become subsumed under it."

As class society develops individuals become "subsumed" to their class. Subsume means to be incorporated into something more comprehensive. Social classes are more comprehensive than individuals. This process includes being subjected to all sorts of (bad) ideas. Marx's words here are, "We have already indicated several times how this subsuming of individuals under the class brings with it their subjection to all kinds of ideas, etc."

Marx is clear about the sort of society (communism, a society without a ruling class) we would need for this process of individuals being subsumed to classes to come to an end:

"This subsuming of individuals under definite classes cannot be abolished until a class has taken shape, which has no longer any particular class interest to assert against the ruling class"

As capitalism develops one of the main things denying individual freedom is the division of labour which develops as part of the capitalist system

To abolish division of labour and to make personal freedom possible requires a true community where an individual has the means of cultivating his gifts in all direction through free association with others in the community.

But community under capitalism is illusory except for the privileged. For the majority it becomes a new fetter because of capitalist social relations, which includes barriers arising from wealth disparity and the above mentioned division of labour.

Consequently, under capitalism within individual life there appears a division between the personal, on the one hand, and that which is determined by the division of labour, arising from the needs of the capitalist system, on the other hand. Persons are still persons but their personality is largely determined by their position in class society.

Under capitalism where individuals end up is largely "accidental" (random). You don't develop as a fully free individual because to survive under capitalism means you have to slot yourself somewhere into the capitalist inspired division of labour.

Individuals might think they are free because where they end up is accidental but in reality they are less free (than under earlier social systems) because they are subject to "the violence of things". Perhaps this anticipates Marx's later analysis of commodity relations, which describes the replacement of human relationships with the relationship between things.

Proletarians have no control over their social destiny, they are sacrificed from youth and their condition of life is forced upon them

Only revolutionary proletarians are free individuals since they understand the need to overthrow capitalism

What is called personal freedom is controlled by the existing productive forces and forms of intercourse at any particular time

My comment on this summary:

Today, in a relatively wealthy society such as Australia, people who fit the Marxist description of "proletarians", eg. teachers who don't own the means of production, have all sorts of freedoms that were not present when this was written, 170 years ago. People can work hard in a profession they choose, pay off the mortage (20+ years), have a family, send their kids to elite Private schools if they can afford it, choose their entertainment, donate to charities or volunteer to help the poor, travel the world and retire at 60 or younger to relax in their declining years. Such a life is lived by many. It is the best that capitalism can offer the proletarians of today.

People usually feel that they choose their profession as free individuals. However, I feel that Marx is right and that this feeling is at best only partly true. People find a niche, a "good job" (engineer, maths professor, social worker) within the capitalist system that meets their needs for money (can't live without it), social status / satisfaction. But this division of labour is largely determined by social and educational background. Not many lawyers come out of government schools. Once they are in a good job then people rationalise their position. "My job is socially useful and of benefit to others". Alternatively, "I have worked hard all my life and will enjoy the benefits of my hard work". In the meantime the capitalists do what they do best, find ways to invest and accumulate more capital (James Packer casinos, Twiggy Forest mining, Bill Gates computing etc.). They live in a totally different world. The class division is very real but over time most of us just come to accept it, that is the way things are, get on with your life. But why should we accept it? A better society can be imagined and was imagined by Marx, even though there have been all sorts of problems when revolutions try to go there.

So, we don't have the true community that Marx envisaged. James Packer isn't going to invite me over to his mansion for a cuppa tea and give me advice about how to earn my next million so I can retire early too. I don't have the same sort of freedom that he has to choose my developmental path. This did come about accidentally. He was Frank Packer's son and I wasn't. There was something more involved here than a free choice to become filthy rich. The ability of people to do their own creative and rewarding thing, whatever it is, is severely constrained by their income.

However, it appears to be exaggerated rhetoric to claim that community under capitalism is illusory. People join various clubs (footy, book, chess, Facebook etc.) and enjoy themselves with friends. This is not an illusion. I think Marx is suggesting we can do better, much better, that we need to open our eyes wider and see the injustice and exploitation in society as a whole and get to the root of that.

In capitalist society, we all have to live parallel lives as Marx suggests, one personal (private family, friendship circle, personal introspection) and one public (our life at work where we earn the money to continue or standing in a queue at Centre Link)

One common criticism of Marx centres around his alleged lack of recognition of the individual, the lack of individual freedom in the Soviet Union during the Stalin years, for example.

What I notice here about the text is that Marx does provide quite a bit of wriggle room for the bourgeoisie to be individuals both through competition (which can't be avoided within capitalism) and choice. He specifically rejects the formulation "that bourgeois is only a specimen of the bourgeois species".

It is true, however, that proletarians, in relatively wealthy Australia, have more wriggle room and some, although limited, freedom of choice, than is suggested in Marx's writing of 170 years ago.

the core problem with marxism

I have put the following post up on reddit (link) for discussion. Comments here are welcome but I expect there will be more discussion there than here.

I'll try to articulate a critique of marxism that makes sense to me. Marxism was developed in the 19th Century when Reason and Science as a conquering force from the Enlightenment, which more or less overwhelmed religious belief, was seen as either a higher form of thought or at least a sufficient form of thought to solve all the significant problems in the world. Marx called his form of socialism "scientific" in contrast to utopian socialism. Marx's historical and dialectical materialism was influence by Hegel's idea that there were clear historical laws which, with much effort, could be discovered, articulated and provide a guide to scientific action.

When you put together the overarching concept of "scientific socialism", combined with a monistic (rather than pluralism) One TrueWay world view, expounded by Plekhanov and adopted by Lenin, and further combined with a (perhaps unconscious) fact-value or science - ethics dichotomy (rather than a distinction) then you end up with an overly deterministic way of evaluating how the world works.

Engels said that freedom is the recognition of necessity and this is the marxist view of virtue or ethics. This downplays the importance of ethics in our thinking in general and provides a basis for totalitarianism. The quickest way to achieve justice for the oppressed is to seize political power by whatever means available and implement the socialist order.

The "necessity" of overthrowing capitalism by revolution and establishing a dictatorship of the proletariat has led in practice to a dictatorship by the communist party. Democracy is denied since the masses are denied the right to reintroduce capitalism if 51% desire that. Communists are not the best democrats. Unfortunately, in practice, this has led to the Gulag (1). The historical facts have been endlessly debated, disputed, interpreted and reinterpreted. Marxists always admit that errors have been made but they can be corrected. What I am trying to outline here is the underlying cause, an overestimation of the role of Science as in "scientific socialism".

My argument here is not that any particular or detailed contribution by Marx is clearly wrong. For instance, Capital in my view is a brilliant critique of the political economy. It is also true that at certain times in history there was little alternative but to become a communist. If you were a Jew, or indeed any decent person, in Europe facing the rise of the National Socialists in the 1930s the only good options were to become a communist, since the alternative opposition was pathetic, or run away.

I am not arguing that capitalism is a good system. Capitalism is a terrible system. It is just that all the alternatives we have tried so far have turned out to be worse. (to paraphrase Winston Churchill)

This is a philosophical critique. Dialectics and Logic, the tools of scientific socialism are very useful and have their place in good analysis. It is just that they do not and cannot provide a One True Way forward. The core problem is that Marxism was built on a theory of the role Science that was plausible in the 19th Century but which we need to re-evaluate today.

(1) update 9th September 2014: My understanding now is that gulag's existed in Stalin's USSR but not in Mao's China. Red Guards being sent to the countryside at the end of the Cultural Revolution as a policy decision to narrow the city-country gap is a different concept to a gulag (prison with forced labour). The Red Guards in China's countryside were not detained there against their will, long term.

Lysenko Affair analysis by Helena Sheehan

I've always had difficulty understanding the varying histories or recommendations about the history of the USSR. "Stalin good"; "Stalin bad, Trotsky good"; Koestler's "Darkness at Noon"; George Orwell's "Animal Farm"; "a Stalin led USSR defeated the Nazis"; "Stalin 70/30"; "Read more recent post archive opening histories"; "History is written by the winners" etc. Call me naive. You might think you understand it but I never have.

The author's or recommender's POV (Stalinist, Trotskyist, anti-marxists, liberals, humanists) always seem to overwhelm the complexity of the data. For many years I have put these questions into the too hard basket and remained a "doubtist".

So, what appeals to me about a scientific history is that the data and hence the interpretation is relatively harder. Science has clearly progressed a lot in the past 150 years (going back to Marx and Engels) whereas "progress" in economics and politics, it could be argued, is more like heading off in tangents or going around in circles. Progress in science can't be denied (even though the philosophy of science remains a difficult area) whereas progress in economic and politics is debatable eg. standard of living has gone up but the gap b/w rich and poor has widened.

Helena Sheehan has been strongly influenced by marxism and also remains open minded to different interpretations. As argued above I think her general framing of how to assess the history of marxism and the philosophy of science is a good one.

I'd strongly recommend Chapter 4, The October Revolution: Marxism in Power (the book is here). [So far I've read Chapters 1 (Engels) and 3 (Lenin's Materialism and Empirio Criticism) as well,which are also good]. In Chapter 4 she traces the evolution of the various currents that eventually led to Soviet State support for Lysenko's phoney science. Briefly, Lysenko promoted Lamarkism and opposed Genetics. After 1935 in the USSR ideological demogoguery progressively replaced useful, scientific, vigorous debate - at great and tragic cost.

It does make for grim reading in parts. It has helped me assess a part of history I've always felt uncertain about. It reveals the sorts of arguments and thinking behind them, used by both sides of the science debate, before the crude politics of power took over. I plan to delve into the style of discussion more: arguments that sound good at the time but turn out to be wrong (not finished yet). My motivation is an interest in what it means to have a scientific understanding of the world in a broad sense - and how that sometimes or often becomes derailed.

Marxism and the Philosophy of Science by Helena Sheehan (introduction)

Marxism and the Philosophy of Science by Helena Sheehan

On page 10 (introduction) Helena outlines 5 different types of errors in interpreting the history of Marxism (I've rephrased it a bit since I found her words initially not clear)

1) unproblematic straight line correctness

2) it would have been an unproblematic straight line except for the Stalin "cult of the personality" problem

3) Certain heretical critics (eg. Lukacs) provide a reinterpretation of Marxism which is then accepted uncritically

4) Selected Marxist texts are given forced "readings" and then other interpretations are dismissed as "historicist". An Althusserian once said to the author, "There is no such thing as history; there are only books on shelves", which left her speechless.

5) The whole of Marxism is dismissed as the "illusion of the epoch" (reference to a book by HB Acton)

On page 12, in contrast, she outlines her approach to the history of Marxism:

1) It's essential to delve into the "difficult matters" and "the self inflicted tragedies of the communist movement" ... she disagrees totally with "the premises underlying the tradition of sacrificing truth to 'partisanship', in the name of which so many crimes against science and against humanity have been committed"

2) Even without Stalin the history of Marxism would not be an unproblematic straight line (obvious)

3) She disagrees with the tendency of those who draw a sharp line b/w "creative" Marxists - Marx, Lukacs, Korsch and Gramsci - on one side and "dogmatic" Marxists - Engels, Lenin, Stalin - on the other side. Good and bad philosophers can be found on both sides of this divide. She likes Gramsci and Caudwell.

4) She is an unrepentant historicist - we cannot separate human thought from the context of human thinking without thoroughly distorting what it is. She adds in a footnote that such interpretations are not in opposition to structural, logical or systematic explanations.

[ on page 16 she elaborates further on her historical perspective: "Most philosophers today are utterly oblivious to the fact that philosophy or science is historical, except in the most trivial and superficial sense. Even when they do look at the history of philosophy or science they do so in such a thoroughly ahistorical and noncontextual way, that anybody could virtually have said anything at any time. In philosophy, the ideas of Plato, Aristotle, Descarte, Hume, Kant, Hegel, Carnap and Quine are treated as discrete and interchangeable units, virtually independent of time and place ..."]

5) Rather than an "illusion of the epoch" she believes that however problematic Marxism remains (quoting Sartre) the unsurpassed philosophy of our time because of such features as its comprehensiveness, coherence and orientation towards science.

My thoughts: There may be more than 5 ways to misunderstand the history of marxism. I don't know enough to say whether her judgements about Gramsci and Caudwell as "the good guys" are correct or whether she is even looking in the right places to find answers. However, I do very much like her general framing of how to approach the history of marxism:
- the need to look into the dark places, to assess negatives as well as positives
- those who make errors may also have redeeming features; those who are mainly correct have probably also made important mistakes; we need to avoid the tendency of making black and white evaluations; nevertheless, categories such as correct and incorrect, friend and enemy are still valid categories in history and politics
- there is something about marxism (not yet identified here) that makes it worth pursuing as a key method of thinking to both understanding history and solving current world problems; to confuse errors, even very significant errors, with a fundamentally flawed philosophy would be an even bigger mistake

overcoming narrow economics inertia

Because of the 2008 economic crisis I decided to study political economy seriously, something which I had previously put into the too hard basket. This study was and is difficult for me and was proceeding too slowly so I have taken time off work this year to move it along.

After over 6 months of reading and searching I have finally found a modern book which meets my needs:

From Political Economy to Economics: Method, the social and the historical in the evolution of economic theory by Dimitris Milonakis and Ben Fine. Check out the contents page at this amazon link using their look inside feature (one page of contents is missing at google books, why do they do that?)

I'm about a third of the way through but have read enough to say it is very good.

Tracing the history of how the methodology of economics went so wrong provides insight into a big part of the solution of what to do to repair the enormous damage that has been done. And the damage goes back over a century. Obviously there is a need to make many new economists political economists who understand how it should be done, rather than universities continuing to churn out narrow econometrics experts, who don't understand the big picture. How are we going to overcome a hundred years of narrow economics inertia? Make a start by buying and reading the above book.

btw I'm now buying books through The Book Depository since they have free delivery, which saves a lot.

kay and van dam discuss engelbart's ideas

Program for the Future (video, about 80 minutes) where Alan Kay and Andy van Dam discuss Doug Engelbart's ideas in celebration of the 50th anniversary of the mother of all demos

(I picked this up from mark miller's site: Tales of inventing the future)

This video is very good, hard hitting analysis about how great visions can be spoiled, that we could have done better. Everyone knows that Engelbart invented the mouse but his broader vision has been largely forgotten. Engelbart is present and is treated with great respect and affection by both speakers.

Some of the ideas mentioned here, briefly. Try to make time to view the whole thing for some high level, stimulating discussion. I'd like to transcribe some sections but am too pushed for time at the moment.

The need to remain focused on the high level goals: augmentation of human intellect (Engelbart) and human-computer symbiosis (Licklider)

It's difficult to capture and summarise group wisdom, more needs to be done. Google searches are crude.

Putting training wheels on bikes diminishes the efficiency of a bike. Computer systems are like that today, keeping users at a baby level (at 32 minutes)

We are wedged today in the way computers are designed both conceptually and technically. We might as well burn the whole thing and start again.

Pop culture is to be incurious about the past and the future

A big problem with the web is that the browser removed WYSIWIG functionality. Hardly anyone complained.

engelbart: co-evolution of humans with machines

It's hard or impossible to imagine a world without all the things that Doug Engelbart demonstrated at his 1968 mother of all demos ("... a computer mouse, which controlled a networked computer system to demonstrate hypertext linking, real-time text editing, multiple windows with flexible view control, cathode display tubes, and shared-screen teleconferencing" 40th Anniversary)

But with respect to his vision it does seem clear that we have become far too techno-centric in the way we conceptualise the computer - as a bunch of more or less independent applications to get various jobs done, rather than as an integrated vehicle to augment our co-evolution.

By 1959 he had enough standing to get approval for pursuing his own research. He spent the next two years formulating a conceptual framework for a new discipline that became the guiding force for his 1962 seminal work, "Augmenting Human Intellect: A Conceptual Framework," ...

Concepts such as augmenting human intellect, improvement infrastructure, co-evolution of artifacts with social-cultural language-practices, and bootstrapping evolved directly from this work, as did the following twenty years of applied co-evolution. Motivating that framework were, and still are the assumptions that complexity and urgency are increasing exponentially and that the combination of these two will soon challenge our organizations ...

A myriad of technical and non-technical elements came into play, such as tools, media, language, customs, knowledge, skills, procedures, and so on. He perceived that these elements had co-evolved slowly over centuries, but that with the explosive emergence of digital technology, the technical elements would shoot way ahead of the non-technical and cause a trend toward automating rather than to augmenting peoples' activities
- A Lifetime Pursuit by Christina Engelbart

reading Minsky

The Emotion Machine by Marvin Minsky

Minsky has studied many great writers who have thought deeply about the human mind. Not only contemporary thinkers but he ranges across the centuries (Aristotle, Augustine, Descarte, Darwin, Franklin, Poincare, Freud etc.). Many of the sections of his book begin with quotations and summaries from these writers and then proceed onto Minsky's own independent evaluation of them.

To provide just one example (there are many) in section 7-7 he uses quotations from a book written by Henri Poincare in 1913 as the basis for a discussion and presentation of his own views on a 4 stage model of unconscious processes (preparation, incubation, revelation and evaluation)

In reading Minsky, carefully, I obtain a strong feeling that I am receiving a distillation of some of the best thoughts from the best thinkers in human history from one of the current best thinkers who also happens to be a great writer

As well as that I'm discovering a very plausible view of what the research agenda for our understanding the mind ought to be.

I've been summarising some of it on the learning evolves wiki. In some ways it's a deceptively simple book but quite hard to hold all of it in your mind as an integrated whole.

what is maths? Paul Lockhart's Simplicio-Salviato dialogue

Lockhart's Lament (pdf 25pp) introduced by Keith Devlin

"Maths is the music of reason"

This beautifully written lament takes some powerful swipes at school maths, textbooks, our suppression of the drama of maths history, our collective cultural ignorance of maths (we think we know but we don't) and supplies some great examples of real maths teaching (the triangle in a box problem, the sum and difference of two numbers problem)

Simplicio and Salviato were two characters used by Galileo in his polemic against the Church. Paul Lockhart uses the same characters to construct a modern day polemic about the organised, uninspiring religion of standardised School textbook maths.

Simplicio is a "back to basics", instructionist, consumer-oriented, career-oriented defender of the traditional maths curriculum. Salviato is a passionate advocate of exploration and discovery - maths as an art form.

SIMPLICIO: All right, I understand that there is an art to mathematics and that we are not doing a good job of exposing people to it. But isn’t this a rather esoteric, highbrow sort of thing to expect from our school system? We’re not trying to create philosophers here, we just want people to have a reasonable command of basic arithmetic so they can function in society.

SALVIATI: But that’s not true! School mathematics concerns itself with many things that have nothing to do with the ability to get along in society — algebra and trigonometry, for instance. These studies are utterly irrelevant to daily life. I’m simply suggesting that if we are going to include such things as part of most students’ basic education, that we do it in an organic and natural way. Also, as I said before, just because a subject happens to have some mundane practical use does not mean that we have to make that use the focus of our teaching and learning. It may be true that you have to be able to read in order to fill out forms at the DMV, but that’s not why we teach children to read. We teach them to read for the higher purpose of allowing them access to beautiful and meaningful ideas. Not only would it be cruel to teach reading in such a way— to force third graders to fill out purchase orders and tax forms— it wouldn’t work! We learn things because they interest us now, not because they might be useful later. But this is exactly what we are asking children to do with math.

SIMPLICIO: But don’t we need third graders to be able to do arithmetic?

SALVIATI: Why? You want to train them to calculate 427 plus 389? It’s just not a question that very many eight-year-olds are asking. For that matter, most adults don’t fully understand decimal place-value arithmetic, and you expect third graders to have a clear conception? Or do you not care if they understand it? It is simply too early for that kind of technical training. Of course it can be done, but I think it ultimately does more harm than good. Much better to wait until their own natural curiosity about numbers kicks in.

SIMPLICIO: Then what should we do with young children in math class?

SALVIATI: Play games! Teach them Chess and Go, Hex and Backgammon, Sprouts and Nim, whatever. Make up a game. Do puzzles. Expose them to situations where deductive reasoning is necessary. Don’t worry about notation and technique, help them to become active and creative mathematical thinkers.

SIMPLICIO: It seems like we’d be taking an awful risk. What if we de-emphasize arithmetic so much that our students end up not being able to add and subtract?

SALVIATI: I think the far greater risk is that of creating schools devoid of creative expression of any kind, where the function of the students is to memorize dates, formulas, and vocabulary lists, and then regurgitate them on standardized tests—“Preparing tomorrow’s workforce today!”

SIMPLICIO: But surely there is some body of mathematical facts of which an educated person should be cognizant.

SALVIATI: Yes, the most important of which is that mathematics is an art form done by human beings for pleasure! Alright, yes, it would be nice if people knew a few basic things about numbers and shapes, for instance. But this will never come from rote memorization, drills, lectures, and exercises. You learn things by doing them and you remember what matters to you. We have millions of adults wandering around with “negative b plus or minus the square root of b squared minus 4ac all over 2a” in their heads, and absolutely no idea whatsoever what it means. And the reason is that they were never given the chance to discover or invent such things for themselves. They never had an engaging problem to think about, to be frustrated by, and to create in them the desire for technique or method. They were never told the history of mankind’s relationship with numbers— no ancient Babylonian problem tablets, no Rhind Papyrus, no Liber Abaci, no Ars Magna. More importantly, no chance for them to even get curious about a question; it was answered before they could ask it.

SIMPLICIO: But we don’t have time for every student to invent mathematics for themselves! It took centuries for people to discover the Pythagorean Theorem. How can you expect the average child to do it?

SALVIATI: I don’t. Let’s be clear about this. I’m complaining about the complete absence of art and invention, history and philosophy, context and perspective from the mathematics curriculum. That doesn’t mean that notation, technique, and the development of a knowledge base have no place. Of course they do. We should have both. If I object to a pendulum being too far to one side, it doesn’t mean I want it to be all the way on the other side. But the fact is, people learn better when the product comes out of the process. A real appreciation for poetry does not come from memorizing a bunch of poems, it comes from writing your own.

SIMPLICIO: Yes, but before you can write your own poems you need to learn the alphabet. The process has to begin somewhere. You have to walk before you can run.

SALVIATI: No, you have to have something you want to run toward. Children can write poems and stories as they learn to read and write. A piece of writing by a six-year-old is a wonderful thing, and the spelling and punctuation errors don’t make it less so. Even very young children can invent songs, and they haven’t a clue what key it is in or what type of meter they are using.

SIMPLICIO: But isn’t math different? Isn’t math a language of its own, with all sorts of symbols that have to be learned before you can use it?

SALVIATI: Not at all. Mathematics is not a language, it’s an adventure. Do musicians “speak another language” simply because they choose to abbreviate their ideas with little black dots? If so, it’s no obstacle to the toddler and her song. Yes, a certain amount of mathematical shorthand has evolved over the centuries, but it is in no way essential. Most mathematics is done with a friend over a cup of coffee, with a diagram scribbled on a napkin. Mathematics is and always has been about ideas, and a valuable idea transcends the symbols with which you choose to represent it. As Gauss once remarked, “What we need are notions, not notations.”

SIMPLICIO: But isn’t one of the purposes of mathematics education to help students think in a more precise and logical way, and to develop their “quantitative reasoning skills?” Don’t all of these definitions and formulas sharpen the minds of our students?

SALVIATI: No they don’t. If anything, the current system has the opposite effect of dulling the mind. Mental acuity of any kind comes from solving problems yourself, not from being told how to solve them.

SIMPLICIO: Fair enough. But what about those students who are interested in pursuing a career in science or engineering? Don’t they need the training that the traditional curriculum provides? Isn’t that why we teach mathematics in school?

SALVIATI: How many students taking literature classes will one day be writers? That is not why we teach literature, nor why students take it. We teach to enlighten everyone, not to train only the future professionals. In any case, the most valuable skill for a scientist or engineer is being able to think creatively and independently. The last thing anyone needs is to be trained.

I love this essay but also have a few brief critical comments:

(1) In the above dialogue in response to Simplicio's point that children cannot rediscover the Pythagorean theorem unaided, Lockhart, speaking through Salviato responds:

Let’s be clear about this. I’m complaining about the complete absence of art and invention, history and philosophy, context and perspective from the mathematics curriculum. That doesn’t mean that notation, technique, and the development of a knowledge base have no place. Of course they do. We should have both. If I object to a pendulum being too far to one side, it doesn’t mean I want it to be all the way on the other side. But the fact is, people learn better when the product comes out of the process.

I agree with what Lockhart is saying here but I don't think he sticks to this position consistently throughout his essay. In his passionate enthusiasm for maths as an art form he does let the pendulum swing too far one way. I would say he more or less denies the importance of behaviourist learning (see Dennett) and doesn't grasp that what works for the creative student does not work for all students.

Open ended discovery learning is another possible road to purgatory. To draw an example from the language wars. Whole language techniques may work well for many students but other techniques (phonics) are essential for the other 25%. According to Kevin Wheldall, "25 per cent of low-progress readers will fail to learn to read if they do not have systematic instruction using phonics" (source)

(2) Lockhart is wrong to imply that other subjects are not butchered by School

(3) Papert's constructionist use of logo programming does open up a possible pathway to solve some of the problems identified by Lockhart but this is not even mentioned