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Artificial intelligence (AI) is an attempt to replicate human intellectual capabilities in machines. It encompasses various aspects such as facial recognition software, natural language processing, and deep learning techniques. However, the scholarly and technological definition of AI may differ from the public's conception. Machine learning is a subset of AI, focused on designing systems that reproduce human abilities like classification and pattern recognition. AI has been integrated into everyday life, from spell check and Netflix recommendations to the functioning of smartphones and Amazon. Despite its widespread use, AI is often unnoticed or misunderstood by the general public.
Predicting the future is a challenging task, and linear extrapolation from current trends often leads to inaccuracies. Scenario planning, which involves considering multiple potential futures, helps in understanding the complexity and uncertainty of the future. Science fiction often presents both utopian and dystopian scenarios, reflecting societal hopes and fears. AI is no exception, with narratives ranging from the fear of a robo-apocalypse to the optimistic vision of advanced technology improving society. The key is to strike a balance between embracing the potential benefits of AI while critically examining its potential risks and implications.
Cultural context plays a significant role in the acceptance and perception of AI. While some cultures may have a history of animistic beliefs, resulting in more openness towards robotic companions, the acceptance and understanding of AI is not solely determined by culture. In Western societies, people often have implicit animistic relationships with AI assistants and interact with AI devices without recognizing it. Media representations, such as movies like Terminator, often shape public discourse and exaggerate AI's capabilities. Public understanding of AI is crucial for informed decision-making, similar to climate change, but there is still much work to be done in raising awareness and promoting responsible AI use.
The podcast episode explores the challenge of engaging the public in discussions about AI due to prevalent dystopian or utopian narratives in the media. While academics try to promote a more nuanced understanding, they face the issue that AI may mean little to most people. The lack of a common understanding necessitates more education on AI ethics and transparency. Initiating discussions and debates is crucial in establishing digital trust and addressing concerns about privacy, surveillance, data ownership, and security.
The podcast delves into the connection between AI and religious or cultural beliefs. The realization that humans imbue AI systems with their own values raises questions about the sources of AI's moral foundation. Different religious and cultural groups offer diverse approaches, ranging from deontological rules to suggestions for ethical regulation. However, the complexity of embedding values into AI systems highlights the need for ongoing dialogue and education on ethics, considering both individual moral systems and societal values.
Artificial Intelligence can be found in every aspect of our lives. From A-level grade predicting algorithms to Netflix recommendations, AI is set to change the choices we make and how our personal information will be used. In this episode, we explore the future of AI - its potential benefits and harms - with our three guests. Beth Singler told us about the different cultural consequences of AI, and how the way we think about the future of AI reflects more about society today than the future itself. John Zerilli shared his views on the consequences of AI for democratic decision-making, and Richard Watson urged us to conceive of the future of AI in terms of ‘scenario planning’, rather than predicting the future directly. We cover topics ranging from how to make AI ‘ethical’, how the media representation of AI can colour the public’s perception of what the real issues are, and the importance of an international AI regulatory system.
This episode was produced by Nick Saffell, James Dolan and Naomi Clements-Brod. Annie Thwaite and Charlotte Zemmel provide crucial research and production support for Series 2.
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Timestamps:
[0:00] - Introductions
[01:22] - guest research introductions
[01:55] - what is AI?
[02:46] - machine learning and AI as the same thing?
[04:31] - Artificial General Intelligence (AGI)
[04:47] - AI in our everyday lives- it’s everywhere!
[06:07] - effect of different patterns on AI e.g. COVID-19 anomalies
[06:46] - we need human flexibility to respond to these changing patterns
[07:27] - what is a futurist in residence?
[08:37] - the only certainty with the future is that it is uncertain. There are lots of futures out there. Being a futurist is all about debating and scenario planning
[09:41] - should every organization have an AI and futurist officer?
[10:09]- how we think about the future as reflecting on what we think about the present
[10:54]- Alvin Toffler and 20th-century futurism
[11:55]- futurism and AI. AI dialogue needs to be about its impact on the future
[12:54]- running out of humans?
[13:33]- AI in care homes
[13:38]- Time for the first recap!
[17:55]- the relationship between AI and religion, and the cultural impact of AI
[19:58]- cultural animation and AI receptivity- not a simple relationship
[20:35]- being ‘blessed’ and ‘cursed’ by the algorithm
[22:04]- democracy and AI. How are we to expect citizens to be informed enough to exercise their voting rights in the best way?
[23:28]- Cambridge Analytica and drastic changes in voting. How much does and should the public know?
[25:45]- what opportunities do people have to get informed about AI?
[27:30}- what do the people who are creating AI need to hear?
[27:40]- ‘open AI’ and the need for public access to AI algorithms
[28:59]- Digital trust and who gets to own data
[29:27]- AI and moral responsibility. This is where the religious aspects enter the AI debate.
[30:25]- the ‘deontological approach: building an AI ‘rulebook’
[31:25]- problem with ‘ethical AI’ is that we don’t really know what an ethical human is.
[32:27]- Time for recap number two!
[37:00]- a post-pandemic world and changing human interactions
[38:35]- the ‘Hello Barbie’ robot. Is it socially acceptable for children to be raised by machines?
[39:00]- the hackability of home products
[40:25]- corporations who produce ‘smart’ products can be using data to change our choice architecture
[42:00]- the public understanding of algorithmic bias
[44:06]- media coverage of AI and the fear of apocalypse
[45:01]- loss of free agency… or did we never have any?
[46:00]- to what extent is our skillset being degraded because of AI?
[46:25]- imagining a post-work future. Wall-e or Startrek?
[47:10]- the utopian/dystopian tension
[50:45]- science fiction and its reflective role in society
[52:35]- moving to solutions for combatting AI issues
[53:00]- the importance of regulation and antitrust laws
[55:00]- the tension between national and international AI codes of conduct
[58:05]- Thinking about the benefit of AI can teach us about what makes a good life
[58:20]- concluding summary
Guest Bios:
Beth Singler @BVLSingler is a social and digital anthropologist. She is currently a Junior Research Fellow in artificial intelligence at Homerton College, Cambridge. Her research explores the social, ethical, philosophical, and religious implications of advances in AI and robotics. She has produced a series of documentaries on AI, including “Pain in the Machine”, which received the AHRC Research in Film Award in 2017.
John Zerilli @JohnZerilli is a Research Fellow at the Leverhulme Centre for Future of Intelligence. He is a philosopher with a particular interest in cognitive science, artificial intelligence, and the law. He has an upcoming book entitled “A Citizen’s Guide to Artificial Intelligence”, which is intended to inform the general public on AI. Particularly, he is interested in how well-informed the citizenry has to be in order to make democratic decisions.
Richard Watson is the Futurist-In-Residence at the Entrepreneurship Centre at Judge Business School. His research is focused on technology and the future and how AI will impact businesses and organisations. He founded the website, “What’s Next” in order to help organisations think about the emerging risks and opportunities that AI brings.
Is there any ‘further reading’ you can suggest to listeners?
Book suggestions:
In Our Image by George Zarkadakis.
Will AI Replace Us? by Shelly Fan
AI by Margaret Bowden
2011: Living in the Future (1972) by Geoffrey Hoyle
The Usborne Book of the Future: A Trip to the Year 2000 and Beyond (1979)
What Can't AI do? - https://toptrends.nowandnext.com/2019/10/19/what-cant-ai-do-3/
A ‘map' from 2017 (see top left tech line) https://nowandnext.com/PDF/Mega%20Trends%20and%20Technologies%202017-2050%20(Web).png
Is there any ‘further watching’ you can suggest to listeners?
1929 Metropolis
1934, Master of the World
1956, Forbidden Planet
1966, Colossus: The Forbin Project
1968 2001 a Space Odyssey - HAL 9000
1973, Westworld
1973, The Six Million Dollar Man
1982 – Bladerunner
1983, Wargames
1984, Terminator
1984, Electric Dreams
1985, D.A.R.Y.L.
1986, Short Circuit
1987 Robocop
1999, The Iron Giant
1991, T2
1995, Ghost in the Shell
1999, The Matrix – link to Nick Bostrom
1999, Bicentennial Man
2001, A.I. Artificial Intelligence
2002, S1MONE
2004, iRobot
2008, WALL-E
2009. Moon
2010, Inception
2012, Robot and Frank
212, Prometheus
2013, Her
2014, Transcendence
2014, Automata
2015, Ex Machina
2015, Chappie
2020, Superintelligence
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