Week 8 - Plans and Situated Actions / The Computer in the 21st Century - Ars-onist

Is the situated cognition a true form of intellect?

The discussion about machine and intelligence continues in these next two readings. Us humans take for granted the ability to how we plan or execute actions, and expect the computer to be able to modify and reconfigure situational actions like we do. There is a ‘personification’ we emulate on these objects; it comes to a level that no intellect is recognized without resembling the human thinking. We have big expectations that artificial intelligence and interactive computer systems could perform human intelligence, just as Turing tried to prove with his thought experiment of the Turing machine. Lucy A. Suchman argues that this form of cognition is a mere imitation of intellect. It does not really belong to the intelligence equivalent of the human one as it does not adapt to its dynamic environment. Nevertheless, we have to question this form of situated intelligence as being simply a new trend of today’s society reflecting the major role of interactivity in the tech industry.

The second reading proposes that machines should work as a complement to us and must fade into the background. This is a contrast to Suchman where Weiser notes that we should be free from thinking about the computer and must not have it fully penetrate into human interaction, such as language. The way he proposes we get to it, however, doesn’t fundamentally clash with Suchman: Weiser’s ubiquitous computing system requires a highly competent and flexible user interface to the point that it enhances strongly the interactivity between human and machine.

Week 7 S.H.A.M.E Suchman & Weiser

Suchman challenges the typical eurocentric view of plans as part of action, instead considering them as an after-the-fact visualization of improvised events building towards a goal. This is connected to Weiser's explanation of how technologies can seem to disappear when truly integrated into our lives, for example writing on signs, which we read and act on without even thinking about it.

We should consider both these perspectives when thinking about how AI is built and interacted with. Analyzing different models for the ways in which people make decisions help us understand cognition from various perspectives, and considering how technologies disappear can conversely make us more aware not only of how we can further integrate new technologies into our lives, but also more aware of technologies that are already so integrated we overlook them in our analyses.

Week 6 : Confused Coffee Beans - Neumann and Turing

Across “The Computer and the Brain”, John Von Neumann developed his own critic and conception for the concept of “computation”. Mainly inspired by the work of Alan Turing (Turing Machine) and Claude Shannon (Shannon’s Theorem), Neumann brings five important key ideas of the information age. The first idea of communication through channels and we can all agree that this is quite the basis of computation. Shannon’s theorem gave a remarkably useful way to handle massive chunks of digital data with the minimum loss of information. The second idea, the universality of the computation, is also extremely relevant to the distinction between the human computer and the machine. According to the Church-Turing thesis, a human brain is restricted by natural law, which makes it automatically less powerful than the machine in terms of information-processing, for example, encryption and decryption of digital Nazi languages or data during WWII. The third key idea and probably the most important aspect of computational machines is their architecture. The way machines process with their inputs/outputs, programs, operation codes and the general serial connectivity makes them arguably incompatible to the human’s brain, being an analogue circuit and not digital. The fourth key idea, however, is a contradiction to Ada Byron saying that computers couldn’t think creatively. This concept was already countered earlier by Alan Turing and the “Turing Test”. Neumann’s correlation of the computer and the human neuron system led to the connectionism, which described that computers are built on a neuron model in both hardware and software, so is the human? The final point of Neumann is the concept of “singularity”, a quite scary vision of the runaway of technology over the human race.

For the text of Alan Turing, the approach of what he calls: the “imitation game”, is just impressive. Although many of the digital machines are especially designed for the test, the result are amazingly relevant to the question of : Can machines think ? A digital computer as to learn the instructions to remember it (softwares), however, this is the same principle for the human computer. Turing refers this concept to “instruction tables” or discrete machines. He uses this word because machines are set for a limited number of possibilities, whereas human have more options. Turing brings out many well developed arguments to determine the reliability of the “imitation game”. This sorts out many trust issues around the test, therefore giving the results a certain fiability to show how close the machine computer is from the human one.

Dana Ryashy, Sol Paul, Xavier Champoux, Rose-Marie Dion

VAPC - Week 6 Kurzweil and Turing (Computation II)

Kurzweil's text on the work of John von Neumann investigates an essential equivalence between the human brain and a computer and delves into five key ideas underlying the information age. One of the five core ideas Kurzweil discusses is Turing's concept of the universality of computation, which gets applied to the human brain; essentially, the information-processing capability of a human brain can be matched by that of a machine but can never exceed that of a machine. Or, as is expounded on later in the text, a computer is theoretically capable of simulating the workings of the human brain, but not the other way around. Turing himself discusses the challenges this might present to a machine playing the imitation game, needing to potentially hide it's superior mathematical processing power.

According to Kurzweil, von Neumann was ahead of his time not only as a pioneer in computation, but in terms of his understanding of the field of neuroscience. A central message in Kurzweil's text is the success of applying biologically inspired methods to computation. We discussed the ways this related to both Turing and last week's Penny text. Turing’s text theorizes that a computer can learn and grow “organically” if it were programmed to be raised like a child. The fact that machines can make errors when processing information also adds to their “organic nature”, as it shows that they are imperfect and require improvement. Penny discussed the need to move away from dualist cognitive models towards more embodied understandings of intelligence, highlighting the benefits of modeling machines after humans while warning of the dangers of the reverse. However, in order to model machines biologically, to what degree to we require a computational understanding of biological processes? Is there a way to preserve human experience as the starting point in how we define our relationship to machines, or will attempts to produce artificial intelligence necessarily result in an understanding of ourselves that is more machine-like?

Kurzweil himself believes that the project of artificial intelligence will not displace humans but 'expand the reach of what is already a human-machine civilization'. We wondered what Kurzweil's optimistic view of an expanded civilization might look like, in a context where artificial intelligence can can be assumed to not only match, but exceed the capacities of biological beings?

C+ Gang - The Computer and the Brain | Computer Machinery and Intelligence - Week 6

Question of the week: Is the machine inadvertently superior to the human brain?

We started unpacking this question by differentiating between what machines can do similarly and things it cannot and as we found out, the texts contained more evidence to what can be replicated and imitated. For example, the Kurweill reading says that — among other things — the concept of the universality of computation (his second important idea) can be used in computer intelligence (his fourth important idea) to "conclude that a von Neumann machine can simulate a brain's processing". With that point made clear, we then discussed how the reverse — that a human brain could simulate a computer — is not really possible in most cases. To support this idea, we argued upon the idea of human memory being pretty limited in the sheer amount of things it could remember, a problem not present in machines. For example, there is almost no way someone could remember the contents of every single one of their birthday dinners as we constantly forget unnecessary information of the like. However, a computer would be able to remember right to the amount of strawberries on your 5th birthday cake.

Following that, we also dived deeper into Turing's text, specifically the imitation game and the section on digital computers. When it comes to the imitation game, we understood that it was strictly an exercise in having machines try and behave as a human and not the opposite. In fact, Turing makes it clear that "If the man were to try and pretend to be the machine he would clearly make a very poor showing.", simply because complicated mathematical formulas would be solved instantly by computers whereas a human being would take much longer, among other things. On top of that, the three parts of the digital computer — store, executive unit, control — provide a much better framework for understanding patterns than human memory. So, when it comes to doing a variety of tasks, computers will always be superior. Finally, most of the oppositions we had to the idea, such as machines lacking emotions, were addressed in the section called "Contrary Views on the Main Question".

Week 6: TETRA - Turing and Kurzweil

Are we back in circular thinking that machine computation is projected on human behaviour?

WEEK 6 - The Computer and the Brain - 2ESDAYS

We were really amazed by the foresighted and precedent opinions on the relationship between the computer and the human brain. Von Neumann found that the parallel processing of a great number of neurons in human brains gives human a remarkable power to process information while Turing found that both modern digital computer and nervous system are both electrical. Both of them mentioned Charles Babbage’s Analytical Engine and Lady Lovelace (Ada Byron)’s conclusion that “a computer cannot think creatively.” and “the machine can only do what we tell it to do.” Until today, the machines are still not able to jump off of this rule completely. Turing concluded that the machine can be equal to the brain only when they start to realize what they have done and they are doing it because of their own thoughts and feelings. Maybe the machines in the future may have self-awareness, however, we can never prove it. According to solipsism, “the only way by which one could be sure that a machine thinks is to be the machine and to feel oneself thinking.” In Turing’s fifth arguments from various disabilities, he mentioned that the machines can never have characteristics like beautiful, friendly, have initiative, and have a sense of humor, etc. If we take a look at some recently created robots and AI, their external looking can definitely be described as beautiful, and they can be programmed to be friendly and have a sense of humor. Turing asked at the start of his article that, “Can machines think?”. We believe this question can be rephrased to “Can machine imitate if they are thinking?” And this is also the emphasis of the Imitation Game - it doesn’t matter if the machine is actually thinking, instead, can it pretend to be conscious. We also find the test is meaningless as chatting through machine only shows a very little aspect of information and thinking. The machine functions like a filter that affects our cognition of the information. The interpretation of the same information varies even during human to human communication. Turing’s opinion was too focused on human thinking, he thinks intellectual thinking is the only thing that matters and ignored how important is embodiment and sensations to human. However, the example of Helen Keller was well-made to bring up the connection between the child machine and the children whose senses are being disabled. Both articles finished up on singularity and had an impressive prediction of the outlook of the machines.

Week 6 - “The Computer and the Brain” and “Computing Machinery and Intelligence” by The Visually Impaired

In Alan Turing’s “Computing Machinery and Intelligence.” he discusses the idea of computers, current and future, and their capabilities. At the time, he spoke of computer’s with limited storage and in the imitation game, where computers were to have conversations with an interrogator whom would figure out if the conversation they were having was with a computer or a human. An interesting point he brings up is how the computer must think and act like a human but yet it does things even better than an average human could, for example, quick math, and chess. He speaks of a computer which will be able to add storage to called “infinitive capacity computers” and will be able to imitate humans so well that the interrogators won’t have more than “70 percent chance of making the right identification after five minutes of questioning.”

He then proceeds to discuss the objections to his points that a machine can think. Some that we found interesting is the objection that God only providing thinking to humans only because they have a soul. Though there are complications to this argument regarding animals and women being seen as soulless, thus making them none thinking beings. Second, the consequences of what machines could do if they could think, which he argues that if humans are superior above all then we shouldn’t worry about machines. Third, it discusses that a machine can not provoke or create pieces that will provoke emotions and thought on its own. Though Turing argues that that the imitation game contradicts this statement, computer’s can provide answers that are personal and can provoke emotion such as “ ...By a winter's day, one means a typical winter's day, rather than a special one like Christmas.” “The Computer and the Brain” by Ray Kurzweil discussed computer and the people behind the computers we have today. Our group discussed the history we found interesting. Charles Babbage's Analytic Engine used the idea of the Jacquard loom (which used punched cards to create patterns), as a way to store memory. Sadly, Charles did not have the technology to create his computer and it was lost in time. The great thing that came out of it was the creation of software programming. Lovelace was the first to think about how we can create programs, and the first to start thinking about AI, and started writing programs for the Analytic Engine. She also created the idea of table checking, which is basically debugging in your head. The von Neumann came along and created a form of what we use today. He basically talked about the structure of the brain and how similar it is to a machine/computer. Obviously, he didn't have the correct structure of the brain, but for his time it was pretty miraculous. He outlines Von Neumann discusses neurons and how their output is digital and neuron’s cell body is analog, which is the model software and hardware are built based on. Another thing von Neumann believed was that the brain had the capacity to remember every single detail or our lives. So basically, von Neumann thinks the brain works with memory as 1's and 0's, whereas our brain actually works with recognition. The writer gives a good example of how recognizer recognizes the structure of the letter A, and how at a higher level they recognize the word Apple, and at a comparable level it can recognize the object, and on a higher conceptual level, it can recognize the term "that was funny". When we recall an experience, we know that it's not just a video in our head. It's impossible to remember every single detail because when we revisit the memory, we tend to fabricate some of the events that happened. Also, von Neumann correctly defines the brains powers about how our neurons are able to process information at the same time. It's impossible for one neuron to work, that's why all work is spread throughout all our neurons. The expansion of information is going to grow super fast with our rapid progression with technology. Before brains were a lot more intelligent than computers, however, supercomputers have changed this.

We also compared and contrasted the two texts. Summarizing that Ray Kurzweil is focusing on understanding human intelligence to understand AI and looks more into the human brain itself. While Turing's approach is the imitation test which is used to determine whether or not AI is achieved by a human level of intelligence.

Week 6 - The Computer and the Brain/Computing Machinery - Ars-onist

Is there a definite limit for a computer to imitate the human brain?

The fourth important idea of the information era, according to Kurzweil's introduction to Von Neumann's book, is to "endow computers with intelligence", i.e. to give computers the same thinking capacity as the human brain. This idea is centrally based on Turing's own paper "Computing Machinery and Intelligence". In his paper, Turing claims that instead of questioning if machines can "think" (which could lead to a complicated philosophical debate on the nature of thinking), we should instead consider on whether or not a machine can imitate the human thinker. This is then further elaborated in von Neumann's book, which Kurzweil claims to be exploiting on the computer's potential capacity to accurately emulate the brain’s processing. Turing also makes a brief claim that our conceptions and criticisms of the limits of the computer is just a parallel of the limited storage capacity of decades past, when the typical storage of today were unthinkable. It is still a big debate in our days, however, if computers are (or will) be able to perceive emotions and express them when provided with increasing storage capacity.

On the other hand, Von Neumann underlines that the speed of neural processing is extremely slow which contradicts the race for higher computing power by the use of supercomputers. In order to underline the parallel nature of neural processing, he contrasts the individual neuron latency of the computing in the human brain to its high bandwidth in the throughput of 10^10 neurons simultaneously. By this means, he demonstrate an actual flaw in his computer architecture model which is not imitating the parallel nature of computing in the humans. Nevertheless, he estimates that the supercomputers will be able to simulate the human brain with 10^16 operations per second with the supercomputers in 2020.

Week 6 | S.H.A.M.E | Turing & Kurzweil readings

The first subject that was discussed in this week’s group discussion was the differences between two texts. Kurzweil is interested in how the brain thinks (which would require defining what thinking even is), whereas Turing, believing this question to be fundamentally unprovable, is more concerned with the practical, and provable, question of whether a computer can appear to be thinking. Both approaches are interesting and in our opinion can be considered either together or apart, that is they are not mutually exclusive but consider different parts of the question of artificial intelligence. At its core many elements of the question of artificial intelligence are philosophical and subjective rather than objectively provable scientific fact. For this reason, like with other areas of philosophy, it is important to learn about various perspectives from prominent thinkers, but the final answer can only be a personal one.

Simon Penny - Making Sense - Fantastic 4

Key Question: Penny claims that computation relegates visual and performing arts to second-rate intellectualism. Do you agree?

Penny suggests the dualism between mind and body does not translate into computerized input and output. The material relationship between our mind’s thoughts and our body’s actions is in fact abstract. In the 1980’s due to the surge in microprocessors, technologies got into the hands of those who didn’t fully understand its effect. Thus incorrect assumptions were made about technological culture and how it should be socially integrated. Penny also tactically disarms the notion of cognitivism or mind/body division and discusses the embodiment ideology of sensorial and cognitively being inexorably linked. In how this embodiment fit into the realm of AI Penny explains the notions of intelligence in computers has historically been approached in a Mind over body, penny explains that a logical engine is not capable of processing a world without rules. As humans we problem solve quickly and are adaptable through our senses, true intelligence in AI would have to master the things we do simply.

The visuals impaired~ week 5~ Making sense: cognition, computing, art and embodiment by Simon Penny

In "making sense; cognition, computing, Art, and Embodiment", Simon Penny talks about how computers are cognitive machines. We are one with machines and they are an extension of us. He also talks about how "computing offers new possibilities for new kinds of cultural practices such as social media, online gaming, online chatbots, and global multimedia information exchange" (xxviii). He also talks about dualism of computations, the slang created from computations, and the problematic nature of the dualistic mind frame that is continually promoted because of computation. Essentially, we took words from ourselves to describe machines, and now we are using those changed words to define ourselves in computation terms.

SHAME Penny Simon Reading

Defining cognition for computers and for humans are two different things. The duality explained in the reading comparing body and mind was one of our main topics of conversation during our meeting. How we compare our body and mind with software and hardware. We discussed what are the different stages of life, thinking and cognition and their difference between different animals and robots. The idea of emergence was discussed as being a basic idea of behaviour and basics of intelligence.