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H-AI-BRID
thinking and designing,
Human-AI systems
Overview
• The division between (Phil) Sci and (Phil) Tech
• And the role of instrument in the process of knowledge production
• Re-designing ’knowledge’ in techno-science and the concept of poiêsis
• Poiêsis, from theory to practice
• Re-thinking teaching and learning
• Designing human-AI systems
2
(Phil) Sci -
(Phil) Tech
divide
3
Science ~ Epistêmê
⇌
Technology ~ Technê
4
Phil Science
⇌
Phil Technology
How is knowledge generated
in techno-scientific contexts?
5
What is the role of instruments
in this process?
Two episodes of techno-scientific practices
Computational history of ideas
• Technologies open up novel spaces
for historical investigation
Molecular epidemiology
• Technologies are essential at all
stages, from data generation to
interpretation
6
Why so much
emphasis on
instruments?
Instruments seem to do more than just
• Mediating between us and the world
• Augmenting our capacities to see the
smaller or the bigger
• Enhancing ability to analyse more data
Instruments have a proper epistemic role
in the process of knowledge production
7
ReDiEM Knowledge
Knowledge is a product of techno-scientific activities carried out
by epistemic agents, it is often expressed in propositional form in
natural language, it is also encapsulated in material objects, and
is situated with respect to a number of social, cultural, or
material aspects
Not a definition, but a broad characterisation
• Elements about Relation, Distribution, Embodiment, Materiality are as
important as propositional content and vernacularity
• These elements are interrelated, not isolated; one element can become more
prominent, depending on the specific question at hand
My question, reformulated:
How to cash out the partnership of human and artificial agents in the process of
knowledge production?
8
Poiêsis
Or, how human and artificial epistemic agents co-produce knowledge
The legacy
From Greek thinking:
Poiêsis is about producting artefacts, it is about technê rather than epistêmê
At the root of the (alleged) superiority of epistêmê over technê
From contemporary Philosophy of Information
Poiêsis is (also) about producing the situations moral agents are in, and that are subject
to ethical assessment
Useful to reduce moral luck
10
The semantic space of poiêsis
The poietic character of human epistemic agents:
The production of artefacts by human agents
A topos of Greek philosophy and of philosophy of technology, not my main interest here;
The production of knowledge by human epistemic agents;
An expansion of Phil Information ‘homo poieticus’ as moral agent, it includes human epistemic
agents as techno-scientists and as philosophers
The poietic character of artificial epistemic agents
The power of technical objects to interact and modify the environment
Digital and analogue technologies have this power (in degrees), we learn from Simondon
In techno-scientific contexts, human and artificial epistemic agents produce knowledge together,
With varying contributions, autonomy, agency, …
Entailing important responsibilities, both epistemic and moral ones 11
What’s for?
What can be the use of the
concept of poiêsis, beyond
Phil Techno-Science?
12
Research
What’s the point?
13
Understanding
deepfakes
• Why users trust deepfakes, from a system perspective
• What is the appropriate level of intervention to diminish
the effects of infodemics?
• What is the good use of deepfakes?
14
Analysing deepfakes: at
system level
15
• Visual content
• Disclosure of inauthenticity
• Function of deepfake content
• Representation of target
• Integration of inauthentic content
• Viewing content
• Medium of communication
• Audience reception
• Relationality and framing
• Paratextual knowledge
• Degree of truthfulness
• Perceived identity of target
• Deepfake discourse
• Visual semiotics
• Gender analysis
• Technical features
• …
Teaching
What’s for?
16
How do technologies (have) change(d) our
learning/thinking process?
How to make a balanced use of technologies in
teaching at different levels?
17
How do technologies structure our thinking, writing, speaking?
How to educate/train advanced students and early careers to be self-reflective about the
use and role of technologies
How much technology am I allowed to use? / How much technology do I want to use?
18
To sum up and
conclude
19
Technology has always been with us, and it is here to stay
It has undergone very many changes and transformations, and so it
will be in the future
How can we rethink the human-
technology relationship in terms of
partnership, rather than opposition?
How does this influence
…our research ahead?
… our teaching?
… learning, writing, speaking activities?
H-AI-BRID
thinking, designing, teaching
Human-AI systems
Thanks to Powerpoint Designer for some design ideas

And to my colleagues for taking poiêsis from theory to

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H-AI-BRID - Thinking and designing Human-AI systems

  • 2. Overview • The division between (Phil) Sci and (Phil) Tech • And the role of instrument in the process of knowledge production • Re-designing ’knowledge’ in techno-science and the concept of poiêsis • Poiêsis, from theory to practice • Re-thinking teaching and learning • Designing human-AI systems 2
  • 3. (Phil) Sci - (Phil) Tech divide 3
  • 4. Science ~ Epistêmê ⇌ Technology ~ Technê 4 Phil Science ⇌ Phil Technology
  • 5. How is knowledge generated in techno-scientific contexts? 5 What is the role of instruments in this process?
  • 6. Two episodes of techno-scientific practices Computational history of ideas • Technologies open up novel spaces for historical investigation Molecular epidemiology • Technologies are essential at all stages, from data generation to interpretation 6
  • 7. Why so much emphasis on instruments? Instruments seem to do more than just • Mediating between us and the world • Augmenting our capacities to see the smaller or the bigger • Enhancing ability to analyse more data Instruments have a proper epistemic role in the process of knowledge production 7
  • 8. ReDiEM Knowledge Knowledge is a product of techno-scientific activities carried out by epistemic agents, it is often expressed in propositional form in natural language, it is also encapsulated in material objects, and is situated with respect to a number of social, cultural, or material aspects Not a definition, but a broad characterisation • Elements about Relation, Distribution, Embodiment, Materiality are as important as propositional content and vernacularity • These elements are interrelated, not isolated; one element can become more prominent, depending on the specific question at hand My question, reformulated: How to cash out the partnership of human and artificial agents in the process of knowledge production? 8
  • 9. Poiêsis Or, how human and artificial epistemic agents co-produce knowledge
  • 10. The legacy From Greek thinking: Poiêsis is about producting artefacts, it is about technê rather than epistêmê At the root of the (alleged) superiority of epistêmê over technê From contemporary Philosophy of Information Poiêsis is (also) about producing the situations moral agents are in, and that are subject to ethical assessment Useful to reduce moral luck 10
  • 11. The semantic space of poiêsis The poietic character of human epistemic agents: The production of artefacts by human agents A topos of Greek philosophy and of philosophy of technology, not my main interest here; The production of knowledge by human epistemic agents; An expansion of Phil Information ‘homo poieticus’ as moral agent, it includes human epistemic agents as techno-scientists and as philosophers The poietic character of artificial epistemic agents The power of technical objects to interact and modify the environment Digital and analogue technologies have this power (in degrees), we learn from Simondon In techno-scientific contexts, human and artificial epistemic agents produce knowledge together, With varying contributions, autonomy, agency, … Entailing important responsibilities, both epistemic and moral ones 11
  • 12. What’s for? What can be the use of the concept of poiêsis, beyond Phil Techno-Science? 12
  • 14. Understanding deepfakes • Why users trust deepfakes, from a system perspective • What is the appropriate level of intervention to diminish the effects of infodemics? • What is the good use of deepfakes? 14
  • 15. Analysing deepfakes: at system level 15 • Visual content • Disclosure of inauthenticity • Function of deepfake content • Representation of target • Integration of inauthentic content • Viewing content • Medium of communication • Audience reception • Relationality and framing • Paratextual knowledge • Degree of truthfulness • Perceived identity of target • Deepfake discourse • Visual semiotics • Gender analysis • Technical features • …
  • 17. How do technologies (have) change(d) our learning/thinking process? How to make a balanced use of technologies in teaching at different levels? 17
  • 18. How do technologies structure our thinking, writing, speaking? How to educate/train advanced students and early careers to be self-reflective about the use and role of technologies How much technology am I allowed to use? / How much technology do I want to use? 18
  • 19. To sum up and conclude 19
  • 20. Technology has always been with us, and it is here to stay It has undergone very many changes and transformations, and so it will be in the future How can we rethink the human- technology relationship in terms of partnership, rather than opposition? How does this influence …our research ahead? … our teaching? … learning, writing, speaking activities?
  • 21. H-AI-BRID thinking, designing, teaching Human-AI systems Thanks to Powerpoint Designer for some design ideas  And to my colleagues for taking poiêsis from theory to

Editor's Notes

  1. Humans and technologies have a long-standing relationship of love and hate, fear and hope, trust and distrust. Within digital technologies, AI and generative AI technologies are but the latest (and certainly not last) episode in this sequel. Can we think of Human-Technology relations in terms of partnership, rather than opposition? How? In this talk, I sketch the countours of the concept of ‘poiêsis’, meant to capture the idea of Human-Technology partnership. I will further explore how this idea can be fruitfully used in science and technology education, and also in setting up collaborative projects in the field of digital technologies and AI. === Opening: springer letter. ChatGPT as paradigmatic example Positioning: and and evergreen question for hist/phil sci/tech Cut a long story short: poiesis = how we co-produce knowledge in techno-scientific fields The impact of this idea in teaching: We can teach to reflect on the human-technology relationship, problematizing the de facto partnership We can reflect on the effects on this, e.g. what happens to individualistic scientific culture We can reflect on the role of technology in learning (e.g.: why learning to write? Or to calculate) The potentilal of this idea in setting up new, collaborative research Examples: SOLARIS BEST-HAIBRIDS
  2. HERE GIVE EXAMPLES OF REDIEM-K IN THE 2 CASE STUDIES