luciano.floridi@philosophy.ox.ac.ukwww.philosophyofinformation.net

Luciano Floridi

Research Chair in Philosophy of Information, UNESCO Chair in Information and Computer Ethics

Research Group in Philosophy of Information, University of Hertfordshire

Information Ethics Group, OUCL & Philosophy, University of Oxford

The Beginning: Plato

The Maker’s Knowledge Tradition

Hobbes on Constructionism

Constructionism: Four Consequences

Conceptual Engineering and Computer Science

Six Constructionist Principles

The Turing Test Revisited

Turing Test and Constructionism

Conclusion: back to Plato

Who really knows an artefact?

(A) The imitator, who paints the lyre?

(B) The maker, who builds the lyre?

(C) The user, who plays the lyre? Imitator

artefact

MakerUser

The user possesses better knowledge than the maker.Republic 601a-e; Cratylus 390b; Euthydemus 289b; Phaedrus 274e.

Socrates: Then the sort of knowledge we

require [..] is that in which there happens

to be a union of making and knowing

how to use the thing made. [...]

So we ought, it seems, to aim at

something far other than being lyre-

makers.

Plato, Euthydemus 289b

Problems1.Friendly fire: meant against imitators, ends up being against makers.2.Separation user/maker and lower regard for techne.3.How can God know better despite being the maker/engineer?4.How can conceptual/semantic artefacts be better known by their users?

If genuine knowledge is knowledge of the intrinsic nature of the object known (knowledge of the ontology of the known), we as epistemic agents can only know what we make.

Epistemic research and information modelling: two sides of the same coin.

It is not just seeing but handling that makes a difference.

Constructionism: knowledge is acquired through the construction of semantic artefacts (information modelling).

Of arts some are demonstrable, others indemonstrable; and demonstrable are those construction of the subject whereof is in the power of the artist himself, who, in his demonstration, does no more but deduce the consequences of his own operation.

Hobbes (1656), Six Lessons to the Professors of Mathematics

[Because] the science of every subject is derived from a precognition of the causes, generation, and construction of the same; and consequently where the causes are known, there is place for demonstration, but not where the causes are to seek for.

Geometry therefore is demonstrable, for the lines and figures from which we reason are drawn and described by ourselves; and civil philosophy is demonstrable, because we make the commonwealth ourselves.

But because of natural bodies we know not the construction, but seek it from the effects, there lies no demonstration of what the causes be we seek for, but only of what they may be.

Bacon and knowledge as power – we can improve our knowledge by improving the knowledge of the techniques by which we investigate reality.

Vico and the verum ipsum factum or verum et factum convertuntur (what is true and what is made are interchangeable) – comprehension of the world will fail, so better focus on those sciences whose subject is created by man.

Kant and the noumenon – the ultimate nature of reality in itself remains unknowable.

Friedrich Dessauer – technology establishes a positive contact with noumena.

Black boxes: systems of which we ignore the internal structure, rules and composition.

Things in themselves like black boxes: we can never know their intrinsic nature because we didn’t make them. Constructionism can learn some lessons from Computer Science.

White boxes: systems about which we know everything, because we built them.

4. Confirmation: confirmations or refutations of the hypothesis concern the simulation, not the simulated.5. Non-descriptivism: Reality and Knowledge are in a resource-to-product relation, not original-to-copy or source-to-reproduction relation.6. Economy: the fewer conceptual resources we use, the better it is. (Ockham revisited).

1. Poietic Knowledge: we can know only what we make.2. Constructability: working hypotheses are investigated by (theoretical or practical) simulations.3. Controllability: the simulation has to be controllable.

“Neither machines nor programs are black boxes; they are artefacts that have been designed, both hardware and software, and we can open them up and look inside”.A. Newell and H. A. Simon (1976), Computer Science as Empirical Enquiry: Symbols and Search.

ConstructabilityGiven a theory, we implement and test it in a system.

Controllability

The resulting system is totally controllable, i.e. modifiable, compositional, teleological and predictable.

Modifiablewe can change its internal structures and rules at any time.

Compositional we have control of any single part of the system.

TeleologicalThe system has been built with an intent (maker’s goals) and it acts following an end, though not necessarily intentional (system’s goals).

Predictable

We know the rules of the system, so we can know its behaviour and use it to predict the behaviour of another system or of the natural system that our simulation is trying to model.

Confirmation

Prevents from generalizing the working hypotheses, as if the simulation were THE real cause (or internal structure) of the simulated.

Non-descriptivism

Reality is a resource for our knowledge, not a source of it. Constructionism provides effective methods to work with available affordances and constraints.

EconomyCareful management of resources Green policy. Constructionism seeks the minimal ontological commitment.

Imitation Game aka Turing Test

According to Turing (1950):

“in about fifty years' time it will be possible to programme computers [...] to make them play the imitation game so well that an average interrogator will not have more than 70 percent chance of making the right identification after five minutes of questioning.”

Turing Test:

respects the minimalist criterion

uses the levels of abstraction

is constructionist.

Minimalism. Turing refuses to provide an answer to the question “can a machine think?”. Not well-defined problem because of such vague concepts as “machine” and “thinking”. Imitation Game = better management of resources.Levels of Abstraction. Turing Test is a Level of Abstraction. The rules of the game define the conditions of observability. By changing the rules of the game one changes the LoA so the answer will change too.

Turing refuses to define what “intelligence” really is.Turing refuses to define what “intelligence” really is. Maker’s KnowledgeMaker’s Knowledge

He makes an hypothesis, and devises a system to assess it.He makes an hypothesis, and devises a system to assess it. ConstructabilityConstructability

Turing does not consider those ways requiring a large amount of conceptual resources.

Turing does not consider those ways requiring a large amount of conceptual resources.

MinimalismMinimalism

The fact that a machine passes or fails the test implies only that the machine can, or can not, be considered intelligent at that Level of Abstraction.

The fact that a machine passes or fails the test implies only that the machine can, or can not, be considered intelligent at that Level of Abstraction.

ConfirmationConfirmation

The system is fully controllable.The system is fully controllable. ControllabilityControllability

Turing Test based on Questions and Answers.

Limit: agents not required to ask questions.

To know is to be able to wonder and build semantic

artefacts that can satisfactorily and successfully

address such wonders.

In Plato’s Cratylus (390c)

someone who knows is

defined as: the man who

knows how to ask and

answer questions.

luciano.floridi@philosophy.ox.ac.ukwww.philosophyofinformation.net

Luciano Floridi

Research Chair in Philosophy of Information, UNESCO Chair in Information and Computer Ethics

Research Group in Philosophy of Information, University of Hertfordshire

Information Ethics Group, OUCL & Philosophy, University of Oxford

ACKNOWLEDGEMENTSMany thanks to Jan van Leeuwen, the NIAS-Lorentz Center and everybody else who made the meeting possible.

COPYRIGHT DISCLAIMER

Texts, marks, logos, names, graphics, images, photographs, illustrations, artwork, audio clips, video clips, and software copyrighted by their respective owners are used on these slides for non-commercial, educational and personal purposes only. Use of any copyrighted material is not authorized without the written consent of the copyright holder. Every effort has been made to respect the copyrights of other parties. If you believe that your copyright has been misused, please direct your correspondence to: l.floridi@herts.ac.uk stating your position and I shall endeavour to correct any misuse as early as possible.