Skip to main content

What can Faraday teach us about human responses to AI?


Professor Simone Natale argues that AI resides also, and especially, in the perception of human users. This talk presents materials from his new monograph, Deceitful Media: Artificial Intelligence and Social Life after the Turing Test. This talk is from two years ago and doesn't seem to have attracted the attention it deserves, but serves well today.

Natale begins with an analogy, and a warning from history:

In the middle of the 19th century, a new religious movement called spiritualism began to attract attention. Spiritualists believed that they could communicate with the spirits of the dead, and they would hold seances where they would try to contact the deceased.

One of the leading scientific figures of the time, Michael Faraday, was skeptical of spiritualism. He decided to investigate the matter by conducting experiments and observing seances.

Faraday's investigation led him to conclude that the phenomena at seances were not caused by spirits, but by the participants themselves. He found that people were more likely to experience paranormal phenomena when they were in a suggestible state, such as when they were tired or in a dark room.

Faraday's findings helped to debunk spiritualism, but they also raised questions about the nature of perception and reality. If people can be so easily deceived by their own minds, what else might they be mistaken about?

Faraday's work suggests that we should be careful about what we believe, and that we should always be open to the possibility that we may be wrong.

Natale goes on to talk about talking about the importance of media literacy and how it can help us to understand and critically evaluate the information that we consume.

Whilst on the one hand, AI can be used to create powerful tools that can improve our lives in many ways. On the other hand, AI can also be used to manipulate and deceive us.

Natale argues that it is important to be aware of the potential risks of AI and to use it responsibly. They also suggest that we need to develop new ways of thinking about and interacting with AI in order to maximize its benefits and minimize its risks.

Natale makes a convincing argument that media literacy is essential in the age of AI. AI is becoming increasingly sophisticated, and it is important to be able to critically evaluate the information that we consume, whether it is generated by humans or machines.

Natale also raises some important concerns about the potential risks of AI. They point out that AI can be used to manipulate and deceive us, and that we need to be aware of these risks in order to use AI responsibly. Unfortunately 'Media Studies' is often derided as a 'Mickey Mouse' subject, yet its ability to develop critical thinking as regards the media we consume is going to be more significant now than its ever been. It may only prove a mitigation against the intentional, and inherent, deceptions of AI generated media, but without such mitigations the influences of felonious intents will go unchecked.


Comments

Popular posts from this blog

The Whispers in the Machine: Why Prompt Injection Remains a Persistent Threat to LLMs

 Large Language Models (LLMs) are rapidly transforming how we interact with technology, offering incredible potential for tasks ranging from content creation to complex analysis. However, as these powerful tools become more integrated into our lives, so too do the novel security challenges they present. Among these, prompt injection attacks stand out as a particularly persistent and evolving threat. These attacks, as one recent paper (Safety at Scale: A Comprehensive Survey of Large Model Safety https://arxiv.org/abs/2502.05206) highlights, involve subtly manipulating LLMs to deviate from their intended purpose, and the methods are becoming increasingly sophisticated. At its core, a prompt injection attack involves embedding a malicious instruction within an otherwise normal request, tricking the LLM into producing unintended – and potentially harmful – outputs. Think of it as slipping a secret, contradictory instruction into a seemingly harmless conversation. What makes prompt inj...

The Future of Work in the Age of AGI: Opportunities, Challenges, and Resistance

 In recent years, the rapid advancement of artificial intelligence (AI) has sparked intense debate about the future of work. As we edge closer to the development of artificial general intelligence (AGI), these discussions have taken on a new urgency. This post explores various perspectives on employment in a post-AGI world, including the views of those who may resist such changes. It follows on from others I've written on the impacts of these technologies. The Potential for Widespread Job Displacement Avital Balwit, an employee at Anthropic, argues in her article " My Last Five Years of Work " that AGI is likely to cause significant job displacement across various sectors, including knowledge-based professions. This aligns with research by Korinek (2024), which suggests that the transition to AGI could trigger a race between automation and capital accumulation, potentially leading to a collapse in wages for many workers. Emerging Opportunities and Challenges Despite the ...

Can We Build a Safe Superintelligence? Safe Superintelligence Inc. Raises Intriguing Questions

  Safe Superintelligence Inc . (SSI) has burst onto the scene with a bold mission: to create the world's first safe superintelligence (SSI). Their (Ilya Sutskever, Daniel Gross, Daniel Levy) ambition is undeniable, but before we all sign up to join their "cracked team," let's delve deeper into the potential issues with their approach. One of the most critical questions is defining "safe" superintelligence. What values would guide this powerful AI? How can we ensure it aligns with the complex and often contradictory desires of humanity?  After all, "safe" for one person might mean environmental protection, while another might prioritise economic growth, even if it harms the environment.  Finding universal values that a superintelligence could adhere to is a significant hurdle that SSI hasn't fully addressed. Another potential pitfall lies in SSI's desire to rapidly advance capabilities while prioritising safety.  Imagine a Formula One car wi...