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.


Labels:

Comments

Post a Comment

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...
Post a Comment
Read more

OpenAI's NSA Appointment Raises Alarming Surveillance Concerns

  The recent appointment of General Paul Nakasone, former head of the National Security Agency (NSA), to OpenAI's board of directors has sparked widespread outrage and concern among privacy advocates and tech enthusiasts alike. Nakasone, who led the NSA from 2018 to 2023, will join OpenAI's Safety and Security Committee, tasked with enhancing AI's role in cybersecurity. However, this move has raised significant red flags, particularly given the NSA's history of mass surveillance and data collection without warrants. Critics, including Edward Snowden, have voiced their concerns that OpenAI's AI capabilities could be leveraged to strengthen the NSA's snooping network, further eroding individual privacy. Snowden has gone so far as to label the appointment a "willful, calculated betrayal of the rights of every person on Earth." The tech community is rightly alarmed, with many drawing parallels to dystopian fiction. The move has also raised questions about ...
Post a Comment
Read more

The Hidden Environmental Cost of AI: Data Centres' Surging Energy and Water Consumption

 In recent years, artificial intelligence (AI) has become an integral part of our daily lives, powering everything from smart assistants to complex data analysis. However, as AI technologies continue to advance and proliferate, a concerning trend has emerged: the rapidly increasing energy and water consumption of data centres that support these systems. The Power Hunger of AI According to the International Energy Agency (IEA), global data centre electricity demand is projected to more than double between 2022 and 2026, largely due to the growth of AI. In 2022, data centres consumed approximately 460 terawatt-hours (TWh) globally, and this figure is expected to exceed 1,000 TWh by 2026. To put this into perspective, that's equivalent to the entire electricity consumption of Japan. The energy intensity of AI-related queries is particularly striking. While a typical Google search uses about 0.3 watt-hours (Wh), a query using ChatGPT requires around 2.9 Wh - nearly ten times more en...
Post a Comment
Read more