© Jeroen Goots Professor Lode Lauwaert
Academic year 2025-2026 KU Leuven
PHILOSOPHY OF TECHNOLOGY
,TABLE OF CONTENTS
1 Introduction: concepts .................................................................................................... 4
1.1 Introduction 4
1.1.1 Term/concept/referent 4
1.1.2 Concept 4
1.1.3 Risk of miscommunication 4
1.1.4 Philosophy of technology 4
1.2 Technology 4
1.2.1 Different notions of technology 4
1.2.2 Technology as a thing 5
1.3 Artifical intelligence 5
1.3.1 What is intelligence? 5
1.3.2 What is artificial intelligence? 7
1.4 Philosophy 8
2 Metaphysics ..................................................................................................................... 9
2.1 Introduction to philosophy of mind and AI 9
2.1.1 ‘Metaphysics’ 9
2.1.2 Relationship between metaphysics and ethics 9
2.1.3 Ideas and sensations 9
2.1.4 Why asking both questions? 10
2.2 Thinking 11
2.2.1 What is thinking? 11
2.2.2 (1) Dualism (René Descartes) 11
2.2.3 (2) Alan Turing 13
2.2.4 (3) John Searle 17
2.3 Consciousness 22
2.3.1 Introduction 22
2.3.2 Conceptual clarifications 23
2.3.3 Thomas Nagel (and problems) 26
2.3.4 Can machines have consciousness? 32
2.3.5 Schwitzgebel on alien consciousness 35
2.3.6 Schneider on alien consciousness 37
2.4 Moral ladenness 38
2.4.1 Introduction 38
2.4.2 What does it mean? 39
2.4.3 Arguments pro 41
2.4.4 Arguments contra 42
2.4.5 Critical remarks 44
3 Ethics .............................................................................................................................. 46
3.1 Introduction 46
3.2 Ethics of AI 47
3.2.1 What is ethics of AI? 47
3.2.2 Responsibility 48
3.2.3 Dual use 49
3.2.4 Privacy 49
© Jeroen Goots Philosophy of Technology 2
, 3.2.5 Discrimination 49
3.2.6 Bias 50
3.2.7 Explainability 51
3.2.8 Negativity bias 51
3.2.9 Environmental problems 52
3.3 AI and hermeneutic harm (guest lecture) 53
3.3.1 Primary and secondary harm 53
3.3.2 Relevance in AI-systems 54
3.3.3 Examples 54
3.3.4 Objections 55
3.4 AI’s existential risks 56
3.4.1 Introduction 56
3.4.2 Categorization of AI’s existential risks 58
3.5 Enhancement 63
3.5.1 Preliminary remarks 63
3.5.2 Arguments 64
3.5.3 Assumptions 67
© Jeroen Goots Philosophy of Technology 3
,1 INTRODUCTION: CONCEPTS
1.1 INTRODUCTION
1.1.1 Term/concept/referent
term
- = word/signifier
- e.g. ‘technology’
concept
- = meaning/notion/idea/proposition that is behind the term
- our focus
referent
- = the reality of which one speaks
1.1.2 Concept
= mental representation of properties/qualitities
is always: descriptive
- = how the world is structured
- e.g. chair = object with at least a seat and support
can be: normative
- = how the world should be structured
- concepts can also express evaluation
- e.g. fairness
- e.g. intelligence = implies that it is state that is desirable
1.1.3 Risk of miscommunication
one term, different concepts
two terms, one concept
1.1.4 Philosophy of technology
[1] part 1: technology
[2] part 2: artificial intelligence
[3] part 3: philosophy
1.2 TECHNOLOGY
1.2.1 Different notions of technology
[1] science (cf. Aristotle)
[2] production (cf. Marx)
[3] process: biotechnology, gene technology
[4] things: computers, cars, chatbots, etc. → our notion
© Jeroen Goots Philosophy of Technology 4
, - note: scope can be large or narrow
o e.g. antrophologist will use a large notion of technology (e.g. knife, clothes,
artefacts in general)
o e.g. engineer will use a narrow notion of technology (e.g. a knife is no
technology)
1.2.2 Technology as a thing
consists of 3 qualities
→ = necessary conditions, not sufficient conditions)
1) artificial
o not all artefacts are examples of technology
o all technology is artificial
o note: we need a more precise definition of an ‘artefact’ (e.g. gap in the ozon layer
doesn’t seem like an artefact, although it is a product of humans)
2) function
o developed in such a way that when we use it, we can realise a specific state in
the world
o function ≠ functional → something can be disfunctional and still be technology
because of its being an artefact (e.g. broken watch)
3) material
o artefact that is purely immaterial doesn’t seem like technology
o scientific theory (immaterial) ↔ technological artefact (material)
1.3 ARTIFICAL INTELLIGENCE
1.3.1 What is intelligence?
intelligence is assigned to
1) organic entities
o bacteria, trees, nonhuman animals, humans
2) synthetic entities
o robts
quality – substance
1) quality: property (e.g. tall, red, nice, etc.)
2) substance: material entity
o all properties belong to substance
§ e.g. red is a quality, but it is always something (substance) that is red
o all substances necessarily possess properties
§ e.g. stone always has weight and size
- intelligence:
o is not a substance
o is a property BUT it is substance neutral
§ in any case, intelligence should be assigned to a substance, but it doesn’t
have to be a very specific substance
© Jeroen Goots Philosophy of Technology 5
, § doensn’t matter whether substance is carbon-based or not
§ e.g. an animal, a human, a synthetic entity can be intelligent
- def intelligence = capacity to process input and then realize goals
o there should be input that is processed, leading to the output
o most often used concept of intelligence
o note: no agency needed in order to be intelligent
§ def agency = having the ability to initiate an action
§ decision-maker programs, love AI systems don’t have agency, because
there’s always a human behind it, though they are intelligent
property
- 2 possibilities
1) binary (e.g. truth)
2) gradual (e.g. length)
- intelligence:
o is not binary, is gradual
o decrease/increase is a function of variables that seem to be important in
intelligence:
§ e.g. speed (faster means more intelligent), abstract, complexity
- conseq: artificial intelligence
o is intelligent, although it doesn’t have any agency
goals
- different types of goals
- e.g. physical, social, emotional, cognitive, technical, aesthetic
passive-active intelligence
- passive
o = capacity derived from an external entity
o OR artificial (expert systems)
§ e.g. computer scientist writes code for a system, and the system follow
that rule
o OR natural (bacterial)
§ e.g. a human reflexively withdraws his hand after touching a hot oven
- active
o = capacity acquired through imitation/instruction/exercise
o OR artificial (machine learning)
o OR natural (education)
note: intelligence is also normative (!)
- if I say that X is intelligent, I imply that…
1) X is able to do this (descriptive)
2) it’s good/desirable that X can do this (normative → we praise and stimulate
intelligence)
- ↛ intelligence is moral
o X is not merely good because of intelligence
o however, intelligence can be ethically relevant
© Jeroen Goots Philosophy of Technology 6
, - (good) reasons for praise and stimulation of intelligence:
o collective level
§ 1 IQ point extra among very smartest = $468 extra GDP per person
o personal level
§ the smarter, the higher the income, the happier, the fewer diseases, the
larger the social network
1.3.2 What is artificial intelligence?
definition
- = capacity of an artificial entity, derived or acquired, to realize goals
- ambiguity in literature:
1) AI as a capacity of an artificial system → our notion
2) AI as an ecosystem with capacity (cf. ‘AI systems’ → data centre)
3) AI as a research domain
different meanigs of AI
[1] narrow AI
o = AI with one specific purpose
o most AI systems
[2] aritifical general intelligence (AGI)
o = human level intelligence → able to realize many tasks
§ tasks that are economically relevant
§ note: not clear how many tasks it should be able to do
o consciousness is not a necessary condition for AGI
§ it’s possible that AGI is not conscious
o strong AI is not a necessary condition for AGI
§ weak AI: not able to understand what it’s doing
§ strong AI: able to understand what it’s doing
§ it’s possible that AGI doesn’t understand what it’s doing
o LLMs lie on the border between narrow AI and AGI → more than narrow, but
not yet AGI
o at this point, AGI is only a concept, but we believe that at some point we will
have AGI
§ big companies (like Google, Meta) have AGI as their first purpose
[3] superintelligence
o = explosion of intelligence
o can perform many tasks at an expert level
o at this point, it’s only a concept, but we believe that at some point we will have
superintelligence
two kinds of AI
= two ways of achieving goals
[1] expert systems
o = Good Old Fashion AI (GOFAI)
o rule based: ‘if…, then…’ (mostly)
© Jeroen Goots Philosophy of Technology 7
Academic year 2025-2026 KU Leuven
PHILOSOPHY OF TECHNOLOGY
,TABLE OF CONTENTS
1 Introduction: concepts .................................................................................................... 4
1.1 Introduction 4
1.1.1 Term/concept/referent 4
1.1.2 Concept 4
1.1.3 Risk of miscommunication 4
1.1.4 Philosophy of technology 4
1.2 Technology 4
1.2.1 Different notions of technology 4
1.2.2 Technology as a thing 5
1.3 Artifical intelligence 5
1.3.1 What is intelligence? 5
1.3.2 What is artificial intelligence? 7
1.4 Philosophy 8
2 Metaphysics ..................................................................................................................... 9
2.1 Introduction to philosophy of mind and AI 9
2.1.1 ‘Metaphysics’ 9
2.1.2 Relationship between metaphysics and ethics 9
2.1.3 Ideas and sensations 9
2.1.4 Why asking both questions? 10
2.2 Thinking 11
2.2.1 What is thinking? 11
2.2.2 (1) Dualism (René Descartes) 11
2.2.3 (2) Alan Turing 13
2.2.4 (3) John Searle 17
2.3 Consciousness 22
2.3.1 Introduction 22
2.3.2 Conceptual clarifications 23
2.3.3 Thomas Nagel (and problems) 26
2.3.4 Can machines have consciousness? 32
2.3.5 Schwitzgebel on alien consciousness 35
2.3.6 Schneider on alien consciousness 37
2.4 Moral ladenness 38
2.4.1 Introduction 38
2.4.2 What does it mean? 39
2.4.3 Arguments pro 41
2.4.4 Arguments contra 42
2.4.5 Critical remarks 44
3 Ethics .............................................................................................................................. 46
3.1 Introduction 46
3.2 Ethics of AI 47
3.2.1 What is ethics of AI? 47
3.2.2 Responsibility 48
3.2.3 Dual use 49
3.2.4 Privacy 49
© Jeroen Goots Philosophy of Technology 2
, 3.2.5 Discrimination 49
3.2.6 Bias 50
3.2.7 Explainability 51
3.2.8 Negativity bias 51
3.2.9 Environmental problems 52
3.3 AI and hermeneutic harm (guest lecture) 53
3.3.1 Primary and secondary harm 53
3.3.2 Relevance in AI-systems 54
3.3.3 Examples 54
3.3.4 Objections 55
3.4 AI’s existential risks 56
3.4.1 Introduction 56
3.4.2 Categorization of AI’s existential risks 58
3.5 Enhancement 63
3.5.1 Preliminary remarks 63
3.5.2 Arguments 64
3.5.3 Assumptions 67
© Jeroen Goots Philosophy of Technology 3
,1 INTRODUCTION: CONCEPTS
1.1 INTRODUCTION
1.1.1 Term/concept/referent
term
- = word/signifier
- e.g. ‘technology’
concept
- = meaning/notion/idea/proposition that is behind the term
- our focus
referent
- = the reality of which one speaks
1.1.2 Concept
= mental representation of properties/qualitities
is always: descriptive
- = how the world is structured
- e.g. chair = object with at least a seat and support
can be: normative
- = how the world should be structured
- concepts can also express evaluation
- e.g. fairness
- e.g. intelligence = implies that it is state that is desirable
1.1.3 Risk of miscommunication
one term, different concepts
two terms, one concept
1.1.4 Philosophy of technology
[1] part 1: technology
[2] part 2: artificial intelligence
[3] part 3: philosophy
1.2 TECHNOLOGY
1.2.1 Different notions of technology
[1] science (cf. Aristotle)
[2] production (cf. Marx)
[3] process: biotechnology, gene technology
[4] things: computers, cars, chatbots, etc. → our notion
© Jeroen Goots Philosophy of Technology 4
, - note: scope can be large or narrow
o e.g. antrophologist will use a large notion of technology (e.g. knife, clothes,
artefacts in general)
o e.g. engineer will use a narrow notion of technology (e.g. a knife is no
technology)
1.2.2 Technology as a thing
consists of 3 qualities
→ = necessary conditions, not sufficient conditions)
1) artificial
o not all artefacts are examples of technology
o all technology is artificial
o note: we need a more precise definition of an ‘artefact’ (e.g. gap in the ozon layer
doesn’t seem like an artefact, although it is a product of humans)
2) function
o developed in such a way that when we use it, we can realise a specific state in
the world
o function ≠ functional → something can be disfunctional and still be technology
because of its being an artefact (e.g. broken watch)
3) material
o artefact that is purely immaterial doesn’t seem like technology
o scientific theory (immaterial) ↔ technological artefact (material)
1.3 ARTIFICAL INTELLIGENCE
1.3.1 What is intelligence?
intelligence is assigned to
1) organic entities
o bacteria, trees, nonhuman animals, humans
2) synthetic entities
o robts
quality – substance
1) quality: property (e.g. tall, red, nice, etc.)
2) substance: material entity
o all properties belong to substance
§ e.g. red is a quality, but it is always something (substance) that is red
o all substances necessarily possess properties
§ e.g. stone always has weight and size
- intelligence:
o is not a substance
o is a property BUT it is substance neutral
§ in any case, intelligence should be assigned to a substance, but it doesn’t
have to be a very specific substance
© Jeroen Goots Philosophy of Technology 5
, § doensn’t matter whether substance is carbon-based or not
§ e.g. an animal, a human, a synthetic entity can be intelligent
- def intelligence = capacity to process input and then realize goals
o there should be input that is processed, leading to the output
o most often used concept of intelligence
o note: no agency needed in order to be intelligent
§ def agency = having the ability to initiate an action
§ decision-maker programs, love AI systems don’t have agency, because
there’s always a human behind it, though they are intelligent
property
- 2 possibilities
1) binary (e.g. truth)
2) gradual (e.g. length)
- intelligence:
o is not binary, is gradual
o decrease/increase is a function of variables that seem to be important in
intelligence:
§ e.g. speed (faster means more intelligent), abstract, complexity
- conseq: artificial intelligence
o is intelligent, although it doesn’t have any agency
goals
- different types of goals
- e.g. physical, social, emotional, cognitive, technical, aesthetic
passive-active intelligence
- passive
o = capacity derived from an external entity
o OR artificial (expert systems)
§ e.g. computer scientist writes code for a system, and the system follow
that rule
o OR natural (bacterial)
§ e.g. a human reflexively withdraws his hand after touching a hot oven
- active
o = capacity acquired through imitation/instruction/exercise
o OR artificial (machine learning)
o OR natural (education)
note: intelligence is also normative (!)
- if I say that X is intelligent, I imply that…
1) X is able to do this (descriptive)
2) it’s good/desirable that X can do this (normative → we praise and stimulate
intelligence)
- ↛ intelligence is moral
o X is not merely good because of intelligence
o however, intelligence can be ethically relevant
© Jeroen Goots Philosophy of Technology 6
, - (good) reasons for praise and stimulation of intelligence:
o collective level
§ 1 IQ point extra among very smartest = $468 extra GDP per person
o personal level
§ the smarter, the higher the income, the happier, the fewer diseases, the
larger the social network
1.3.2 What is artificial intelligence?
definition
- = capacity of an artificial entity, derived or acquired, to realize goals
- ambiguity in literature:
1) AI as a capacity of an artificial system → our notion
2) AI as an ecosystem with capacity (cf. ‘AI systems’ → data centre)
3) AI as a research domain
different meanigs of AI
[1] narrow AI
o = AI with one specific purpose
o most AI systems
[2] aritifical general intelligence (AGI)
o = human level intelligence → able to realize many tasks
§ tasks that are economically relevant
§ note: not clear how many tasks it should be able to do
o consciousness is not a necessary condition for AGI
§ it’s possible that AGI is not conscious
o strong AI is not a necessary condition for AGI
§ weak AI: not able to understand what it’s doing
§ strong AI: able to understand what it’s doing
§ it’s possible that AGI doesn’t understand what it’s doing
o LLMs lie on the border between narrow AI and AGI → more than narrow, but
not yet AGI
o at this point, AGI is only a concept, but we believe that at some point we will
have AGI
§ big companies (like Google, Meta) have AGI as their first purpose
[3] superintelligence
o = explosion of intelligence
o can perform many tasks at an expert level
o at this point, it’s only a concept, but we believe that at some point we will have
superintelligence
two kinds of AI
= two ways of achieving goals
[1] expert systems
o = Good Old Fashion AI (GOFAI)
o rule based: ‘if…, then…’ (mostly)
© Jeroen Goots Philosophy of Technology 7
