Pondering AI Kimberly Nevala, Strategic Advisor - SAS

Professor J Mark Bishop reflects on the trickiness of language, how LLMs work, why ChatGPT can’t understand, the nature of AI and emerging theories of mind.
Mark explains what large language models (LLM) do and provides a quasi-technical overview of how they work. He also exposes the complications inherent in comprehending language. Mark calls for more philosophical analysis of how systems such as GPT-3 and ChatGPT replicate human knowledge. Yet, understand nothing. Noting the astonishing outputs resulting from more or less auto-completing large blocks of text, Mark cautions against being taken in by LLM’s disarming façade.
Mark then explains the basis of the Chinese Room thought experiment and the hotly debated conclusion that computation does not lead to semantic understanding. Kimberly and Mark discuss the nature of learning through the eyes of a child and whether computational systems can ever be conscious. Mark describes the phenomenal experience of understanding (aka what it feels likes). And how non-computational theories of mind may influence AI development. Finally, Mark reflects on whether AI will be good for the few or the many.
Professor J Mark Bishop is the Professor of Cognitive Computing (Emeritus) at Goldsmith College, University of London and Scientific Advisor to FACT360.
A transcript of this episode is here. 

Chris McClean reflects on ethics vs. risk, ethically positive outcomes, the nature of trust, looking beyond ourselves, privacy at work and in the metaverse.
Chris outlines the key differences between digital ethics and risk management. He emphasizes the discovery of positive outcomes as well as harms and where a data-driven approach can fall short. From there, Chris outlines a comprehensive digital ethics framework and why starting with impact is key. He then describes a pragmatic approach for making ethics accessible without sacrificing rigor.
Kimberly and Chris discuss the definition of trust, the myriad reasons we might trust someone or something, and why trust isn’t set-it-and-forget-it. From your smart doorbell to self-driving cars and social services, Chris argues persuasively for looking beyond ‘how does this affect me.’ Highlighting Eunice Kyereme’s work on digital makers and takers, Chris describes the role we each play – however unwittingly – in creating the digital ecosystem. We then discuss surveillance vs. monitoring in the workplace and the potential for great good and abuse inherent in the Metaverse. Finally, Chris stresses that ethically positive outcomes go beyond ‘tech for good’ and that ethics is good business.
Chris McClean is the Global Head of Digital Ethics at Avanade and a PhD candidate in Applied Ethics at the University of Leeds.
A transcript of this episode is here. 

Henrik Skaug Sætra contends humans aren’t mere machines, assesses AI thru a sustainable development lens and weighs the effect of political imbalances and ESG.
Henrik embraces human complexity. He advises against applying AI to naturally messy problems or to influence populations least able to resist. Henrik outlines how the UN Sustainable Development Goals (SDG) can identify beneficial and marketable avenues for AI. He also describes SDG’s usefulness in ethical impact assessment. Championing affordable and equitable access to technology, Henrik shows how disparate impacts occur between individuals, groups and society. Along the way, Kimberly and Henrik discuss political imbalances, the technocratic nature of emerging regulations and why we shouldn’t expect corporations to be broadly ethical of their own accord. Outlining his AI ESG protocol, Henrik surmises that qualitative rigor can address gaps in quantitative analysis alone. Finally, Henrik encourages the proactive use of SDGs and ESG to drive innovation and opportunity.
Henrik is Head of the Digital Society and an Associate Professor at Østfold University College. He is a political theorist focusing on the political, ethical, and social implications of technology.
A transcript of this episode can be found here. 

Dr. Mark Coeckelbergh contemplates the messy reality and political nature of AI, the interplay of technology with society, and the impact of AI on democracy.

Patrick Hall challenges data science norms, warns against magical thinking and malleable hypotheses, reflects on human-AI teaming and delivering value with AI.

Fernando Lucini explains the potential applications, pitfalls, and work still to be done to make synthetic data ubiquitous.