Communication and Philosophical Arguments

I’ve never formally studied philosophy. I do, however, have some experience with logic in computer science and engineering contexts. Philosophical arguments may be structured in a similar logical format. This post discusses the approach of communicating philosophical ideas in a structured and logical way that will be tested in upcoming edits and posts on this website.

The structure of a philosophical argument may include premises and conclusions. A premise is a proposed statement of fact. Premises can be combined to make conclusions. An argument may be presented as (numbered) premises and conclusions, a common example being,

P1: All men are mortal.
P2: Socrates is a man.
C1: Socrates is mortal.

Communicating philosophical arguments is a challenge for a number of reasons. Trying to communicate arguments as prose can obscure the important points by burying them in paragraphs and sentences: the structure of an argument, the premises and conclusions, must be extracted.

In future posts and additions to this website, it will be aimed to present philosophical arguments arguments as enumerated lists of premises and the conclusions. Prose may be used to elaborate premises or present thought-experiments that are believed to strengthen arguments; however, clarity and succinctness will still be a goal. Wherever possible summaries will be provided.

As an aside, I have an interest in the practise and failings of debate in general.

I was struck by the exchange of emails between Noam Chomsky and Sam Harris being an example of an attempt at a discussion that struggled to gain traction. Chomsky and Harris both have a great command of the English language, but they seemed to lack a process to conduct a discussion that could allow them to succinctly and accurately communicate their own beliefs and determine the beliefs of the other.

Spoken debates often demonstrate the same failing. A spoken debate may allow the speakers to demonstrate their skill as orators, but the aim should probably be to share and learn from sound arguments. Presently, debates are often a situation where we are subject to the full range of tricks used to persuade. Spoken debates suffer at least two big challenges as a mode of presenting arguments: 1) the audience can only keep a few items in their mind at one time, 2) claims of supporting facts and evidence cannot be checked for truth.

Given that logic is a foundation of modern philosophy it seems odd that its use is not emphasised. The point-by-point approach to expressing an argument seems to provide an improved, straightforward process for conducting debates and discussions. It may be difficult and it may make debates seem even more abstract and dry, but it might improve the value of discussion and debate as a tool for learning.

I’m interested in taking this approach in communicating my philosophical arguments and I hope that it makes any discussion or debates that I have more concise and fruitful.

If all arguments are conveyed as a set of premises and conclusions, anyone with an opposing view should be able to state which premises they do not believe to be true or which conclusions are not valid. Probing the reasons for disagreeing with the truth of a premise or the structure of the argument should lead to a refinement of the argument or adoption of a position that is valid.

In cases where the truth of a statement is not (or cannot) be known, there may be many ways of approaches to find a resolution. It is reasonable to make an attempt to search for evidence that may indicate the truth or falsity of the claim. If evidence is unavailable, experiments may be considered and performed that may provide that evidence. If experiments are not feasible, the effect of truth or falsity on the argument may be examined or an attempt may be made to construct an argument that does not rely on that premise.

Spoken debates may be more educational if conducted with a whiteboard (or similar) used to list the form of arguments made and to act as a visual aid for participants and the audience. Speakers would be required to list the premises and the form of their argument. Responses could come in the form of annotation of the arguments listed, pointing out which claims are dubious or where there is a gap in the argument structure. Evidence and sources could also be provided. This approach would likely change televised debates significantly.

Now that I’ve refined my approach to communication, I just need to actually do some communicating.

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Meaning, Value and Life: Contents

Writing the summary of the Meaning, Value and Life webpage has been difficult to complete. This may be because starting with a summary may be likened to putting the cart before the horse. Finding an effective approach to writing content is an ongoing goal in the development of this website.

Rather than start with a summary, an attempt has been made to draft the section headings of the webpage. The next step will be to fill in the sections with outlines of their contents. These outlines will gradually be replaced with detailed prose.

The section headings and their contents will continue to be subject to revision in the likely event that writing them reveals a clearer and more concise approach to explaining the ideas or, perhaps more likely, making these thoughts precise in writing reveals important gaps. Nevertheless, the list below provides an indication of the future contents of this webpage. The current section headings for the Meaning, Value and Life are as follows:

0. Summary

1. Meaning

This section will explore the concept of “meaning”.

1.1. Usage of “Meaning”

The usage of the word “meaning” will be discussed.

1.2. Examples of Meaning

Things that have meaning will be discussed.

1.3. The Existence of Meaning

When does something have meaning? When does something cease to have meaning? Exploring these questions will provide insights into the nature of meaning.

1.4. Interpretation

The act of interpretation and the importance of interpreters in the existence of meaning will be discussed.

1.5. A Definition of Meaning

From these points a definition of “meaning” will be proposed.

2. Value

This section will explore the concept of “value”.

2.1. Usage of “Value”

The word “value” has many uses. These will be discussed and uses of particular interest will be highlighted.

2.2. Examples of Value

What things have value? What actions are valuable? What are values? Examples of value will be discussed.

2.3. Impetus for Action

The relationship of value to action will be discussed.

2.4. The Existence of Value

How does something acquire value? When does something lose value? The conditions that are necessary for existence of value are discussed.

2.5. A Definition of Value

These discussions lead to a proposal for a definition of “value”.

3. Life

This section will explore the concept “life”.

3.1. Usage of “Life”

The word “life” may have fewer uses but the term is somewhat nebulous.

3.2. Examples of Life

Examples of what is considered to be living provide insights into the necessary conditions for what should be considered alive.

3.3. Alive

The examples of life highlight entities that are on the fringe of being considered alive. When does something qualify as being alive? When does something no longer qualify as alive? This discussion will further dissect the usage of the terms “life” and “alive”.

3.4. The Value of Creating Meaning

Value and action are related to the acts of interpretation and creation that are intrinsic to life.

3.5. A Definition of Life

In conclusion, a definition and meaning of “life” is proposed.

 

Website Revival and New Approach to Developing Content

It has been a long time since the last blog post was published on this website. That hasn’t been for a lack of ideas to write about. It is time to revive this website and try to express and test these ideas and hopefully receive some feedback.

The presentation and development of the website content may be more suited to a persistent webpage format rather than the episodic style typical of blog posts. The current plan is to trial a different process for developing this content:

  1. The main content of this website will be permanent pages that undergo progressive development.
  2. The blog will document this development.

Place-holders for an initial set of pages have been created that will be developed to contain writing on philosophical ideas on a variety of topics:

The next step in the development of these pages will be to update them with a summary of key ideas. Later updates will work on presenting explanations and logical arguments for these ideas.

Feedback is welcome.

Priorities, Hibernation and Twitter

To the few readers of this blog,

I have an important task ahead of me that requires most of my attention, time and energy. That is, completing my PhD will need to be my priority for the next 6 months or more.

Few people are likely to miss my already infrequent posts, but they are likely to become more infrequent. Once my PhD is complete, I hope to embark on some larger projects, posting on the philosophy of mind, the meaning of life, and artificial general intelligence. I will still try to read the posts of other bloggers and comment when possible.

In the meantime, I take public transport, so I may use this time to take up tweeting with more frequency. Sometimes I will tweet links to interesting articles, but I also hope to start tweeting some of my ideas and thoughts.

Questions and comments are still welcome on my blog, but responses may be slow.

[smiley face]

Learning Algorithms for People: Reinforcement Learning

In a previous post I described some simple ways in which learning could be performed algorithmically, replicating the basic process of supervised learning in machines. Of course it’s no secret that repetition is important for learning many things, but the exact way in which we repeat a training set or trial depends on what it is we are trying to learn or teach. I made a series of post on values and reinforcement learning machines and animals, so here I will describe a process for applying reinforcement learning to developing learning strategies. Perhaps more importantly though, I will discuss a significant notion in machine learning and its relationship to psychological results of conditioning — introducing the value function.

Let’s start with some pseudo-code for a human reinforcement learning algorithm that might be representative of certain styles of learning:

given learning topic, S, a set of assessment, T, and study plan, Q
    for each assessment, t in T
        study learning topic, S, using study plan, Q
        answer test questions in t
        record grade feedback, r
        from feedback, r, update study plan, Q 

This algorithm is vague on the details, but this approach of updating a study plan fits into the common system of education; one where people are given material to learn and given grades as feedback on their responses to assignments and tests.

Let’s come back to the basic definitions of computer-based reinforcement learning. The typical components in reinforcement learning are the state-space, S, which describes the environment, an action-space, A, are the options for attempting to transition to different states, and the value function, Q, that is used to pick an action in any given state. The reinforcement feedback, reward and punishment, can be treated as coming from the environment, and is used to update the value function.

The algorithm above doesn’t easily fit into this structure. Nevertheless, we could consider the combination of the learning topic, S, and the grade-system as the environment. Each assessment, t, is a trial of the study plan, Q, with grades, r, providing an evaluation of the effectiveness of study. The study plan is closely related to the value function — it directs the choices of how to traverse the state-space (learning topic).

This isn’t a perfect analogy, but it leads us to the point of reinforcement feedback: to adjust what is perceived as valuable. We could try to use a reinforcement learning algorithm whenever we are trying to search for the best solution for a routine or a skill, and all we receive as feedback is a success-failure measurement.

Though, coming back to the example algorithm provided, considering grades as the only reinforcement feedback in education is a terrible over-simplification. For example, consider the case of a school in a low socio-economic area where getting a good grade will actually get you punished by your peers. Or consider the case of a child that is given great praise for being “smart”. In a related situation, consider the case of praising a young girl for “looking pretty”. How is the perception of value, particularly self-worth, effected by this praise?

Children, and people in general, feel that the acceptance and approval of their peers is a reward. Praise is a form of approval, and criticism is a form of punishment, and each is informative of what should be valued. If children are punished for looking smart, they will probably value the acceptance of their peers over learning. If children are praised for being smart, they may end up simply avoiding anything that makes them look unintelligent. If children are praised for looking pretty, they may end up valuing looking pretty over being interesting and “good” people.

A solution could be to try to be more discerning about what we praise and criticise. The article linked above makes a good point about praising children for “working hard” rather than “being smart”. Children who feel that their effort is valued are more likely to try hard, even in the face of failure. Children who feel that praise will only come when they are successful, will try to avoid failure. Trying to give children self-esteem by praising them for being smart or pretty is, in fact, making their self-esteem contingent on that very thing they are being praised for.

It may seem manipulative, but praise and criticism are ways we can reward and punish people. Most people will adjust their “value-function”, their perception of what is valuable, and, as a result, they will adjust their actions to try to attain further praise, or avoid further punishment. What we praise and criticise ourselves for, is a reflection of what we value in ourselves. And our self-praise and self-criticism can also be used to influence our values and self-esteem, and hence our actions.

A View on the Nature of Consciousness

In the process of communicating with other bloggers that are interested in the future of humanity and philosophy of mind, some upcoming discussions have been planned on a number of related topics. The first topic is: the nature of consciousness and its relationship to the prospect of artificial intelligence. In preparation for the discussion, I’ve summarised my position on this topic here. I’ve spent some time reading and thinking about the nature of consciousness, so I believe that my position has some firm evidence and logical reasoning supporting it. If requested, I’ll follow up with post(s) and comment(s) providing more detailed descriptions of the steps of reasoning and evidence. As always, I’m open to considering compelling evidence and arguments that refute the points below.

The Nature of Consciousness

1. Consciousness can be defined as its ‘nature’. We seem to define consciousness by trying to describe our experience of it and how others show signs of consciousness or lack of consciousness. If we can successfully explain how consciousness occurs — its nature — we could then use that explanation as a definition. Nevertheless, for now we might use a broad dictionary definition of consciousness, such as “the awareness of internal (mental) and external (sensory) states”.

2. Consciousness is a spectrum. Something may be considered minimally consciousness if its only “aware” of external-sensory states. Higher consciousness includes awareness of internal-mental states, such as conscious thoughts and access to memories. Few animals, even insects, appear to be without “awareness” of memory (particularly spatial memory). As we examine animals of increasing intelligence we typically see a growing sets of perceptual and cognitive abilities — growing complexity in the range of awareness — though varying proficiencies at these abilities.

3. Biological consciousness is the result of physical processes in the brain. Perception and cognition are the result of the activity of localised, though not independent, functional groups of neurons. We can observe a gross relationship between brain structure and cognitive and perceptual abilities by studying structural brain differences animal species of various perceptual and cognitive abilities. With modern technology, and lesion studies, we can observe precise correlations between brain structures, and those cognitive and perceptual processes.

4. The brain is composed of causal structures. The collection of functional groups of neurons in the entire body (peripheral and central nervous system) are interdependent causal systems — at any moment neurons operate according to definable rules, effected by only the past and present states of themselves, their neighbours and surroundings.

5. Causal operation produces representation and meaning. Activity in groups of neurons have the power to abstractly represent information. Neural activity has “meaning” due to being the result of the chain of interactions that typically stretch back to some sensory interaction or memory. The meaning is most clear when neural activity represents external interactions with sensory neurons, e.g., a neuron in the primary visual cortex might encode for an edge of a certain orientation in a particular part of the visual field. There is also evidence for the existence of “grandmother cells”: neurons, typically in the temporal lobe of the neocortex, that activates almost exclusively in response to a very specific concept, such as “Angelina Jolie” (both a picture of the actress and her name).

6. Consciousness is an emergent phenomenon.  Consciousness is (emerges from) the interaction and manipulation of representations, which in biological organisms is performed by the structure of the complete nervous system and developed neural activity. Qualia are representations of primitive sensory interactions and responses. For example, the interaction of light hitting the photosensitive cells in the retina ends up represented as the activation of neurons in the visual cortex. It is potentially possible to have damage to the visual cortex and lose conscious awareness of light (though sometimes still be capable of blindsight). Physiological responses can result from chemicals and neural activity and represent emotions.

7. Consciousness would emerge from any functionally equivalent physical system. Any system that produces the interaction and manipulation of representations will, as a result, produce some form of consciousness. From a functional perspective, a perfect model of neurons, synapses and ambient conditions is not likely to be required to produce representations and interactions. Nevertheless, even if a perfect model of the brain was necessary (down to the atom), the brain and its processes, however complex, function within the physical laws (most likely even classical physics). The principle of universal computation would allow its simulation (given a powerful enough computer) and this simulation would fulfil the criteria above for being conscious.

8. Strong artificial intelligence is possible and would be conscious. Human-like artificial intelligence requires the development of human-equivalent interdependent modules for sensory interaction and perceptual and cognitive processing that manipulate representations. This is theoretically possible in software. The internal representations this artificial intelligence would possess, with processes for interaction and manipulation, would generate qualia and human-like consciousness.

Philosophical Labels

I’ve spent some time reading into various positions within the philosophy of mind, but I’m still not entirely sure where these views fit. I think there are close connections to:

a) Physicalism: I don’t believe there is anything other than that which is describable by physics. That doesn’t mean, however, that there aren’t things that have yet to be adequately described by physics. For example, I’m not aware of an adequate scientific description of the relationship between causation, representation and interpretation — which I think are possibly the most important elements in consciousness. Nevertheless, scientific progress should continue to expand our understanding of the universe.

b) Reductionism and Emergentism: I think things are the sum of their parts (and interactions), but that reducing them to the simplest components is rarely the best way to understand a system. It is, at times, possible to make very accurate, and relatively simple, mathematical models to describe the properties and functionality of complex systems. Finding the right level of description is important in trying to understand the nature of consciousness — finding adequate models of neuronal representations and interactions.

c) Functionalism: These views seem to be consistent with functionalism — consciousness is dependent on the function of the underlying structure of the nervous system. Anything that reproduces the function of a nervous system would also reproduce the emergent property of consciousness. For example, I think the ‘China brain’ would be conscious and experience qualia — it is no more absurd than the neurons in our brain being physically isolated cells that communicate to give rise to the experience of qualia.

Changing Views

I’m open to changing these views in light of sufficiently compelling arguments and evidence. I have incomplete knowledge, and probably some erroneous beliefs; however, I have spent long enough studying artificial intelligence, neuroscience and philosophy to have some confidence in this answer to “What is the nature of consciousness and its relationship to the prospect of artificial intelligence?”.

Please feel free to raise questions or arguments against anything in this post. I’m here to learn, and I will respond to any reasonable comments.

Learning algorithms for people: Supervised learning

Access to education is widely considered a human right, and, as such, many people spend years at school learning. Many of these people also spend a lot of time practising sport, musical instruments and other hobbies and skills. But how exactly do people go about trying to learn? In machine learning, algorithms are clearly defined procedures for learning. Strangely, though the human brain is a machine of sorts, we don’t really consider experimenting with “algorithms” for our own learning. Perhaps we should.

Machine learning is typically divided into three paradigms: supervised learning, reinforcement learning, and unsupervised learning. These roughly translate into “learning with detailed feedback”, “learning with rewards and punishments” and “learning without any feedback” respectively. These types of learning have some close relationships to the learning that people and animals already do.

Many people already do supervised learning, although probably much more haphazardly than a machine algorithm might dictate. Supervised learning  is good when the answers are available. So when practising for a quiz, or practising a motor skill, we make attempts, then try to adjust based on error we observe. A basic algorithm for people to perform supervised learning to memorise discrete facts could be written as:

given quiz questions, Q, correct answers, A, and stopping criteria, S
    do
        for each quiz question q in Q
            record predicted answer p
        for each predicted answer p
            compare p with correct answer, a
            record error, e
    while stopping criteria, S, are not met

Anyone could use this procedure for rote memorisation of facts, using a certain percentage of correct answers and a set time as the stopping criteria. However, this algorithm supposes the existence of questions associated with the facts to memorise. Memorisation can be difficult without a context to prompt recall and questions can also help links these facts together. Much like it being common for people to find recall better when knowledge is presented visually, aurally and in tactile formats. The machine learning equivalent would be adding extra input dimensions to associate with the output. Supervised learning also makes sense for trying to learn motor skills, this is roughly what many people do already when practising skills for sports or musical instruments.

It makes sense to use slightly different procedures for practising motor skills compared to doing quizzes. In addition to getting the desired outcome, gaining proficiency also requires the practising the technique of the skill.  Good outcomes can often be achieved with poor technique, and poor outcomes might occur with good technique. But to attain a high proficiency, technique is very important. To learn a skill well, it is necessary to pay attention not only to errors in the outcome, but also errors in the technique. For this reason, it is good to first spend time focusing practise on the technique. Once the technique is correct, focus can then be more effectively directed toward achieving the desired outcome.

given correct skill technique, T, and stopping criteria, S
    do
        attempt skill
        compare attempt technique to correct technique, T
        note required adjustments to technique
     while stopping criteria, S, not met

given desired skill outcome, O, and stopping criteria, S
     do
         attempt skill
         compare attempt outcome to desired outcome, O
         note required adjustments to skill
     while stopping criteria, S, are not met

These basic, general algorithms spell out the obvious of what many people already do: learn through repetition of phases of attempts, evaluations and adjustments. It’s possible to continue to describe current methods of teaching and learning as algorithms. And it’s also possible to search for optimal learning processes, characterising the learning algorithms we use, and the structure of education, to discover what is most effective. It may be that different people learn more effectively using different algorithms, or that some people could benefit from practising these algorithms to get better at learning. In future, I will try to write some further posts about learning topics and skills, and applications for different paradigms of learning, as well as algorithms describing systems of education.