Approaching Irrational Fear over Generative AI: A Fresh Report Advises Policy Makers Against Excessive Reaction
In a recent report, the Centre for Data Innovation has shed light on the current panic surrounding generative artificial intelligence (AI), comparing it to a pattern that has repeated throughout history as new technologies emerge. This pattern, known as the Tech Panic Cycle, is akin to market or moral panics, as well as technology hype cycles.
The Tech Panic Cycle consists of four stages: Discovery/Introduction, Hype and Exaggeration, Panic/Backlash, and Resolution/Normalization. In the Discovery/Introduction stage, a new technology emerges, generating excitement about its potential capabilities. For generative AI, this stage was marked by the debut of models like GPT, showcasing remarkable abilities in content creation, coding, and conversation.
The Hype and Exaggeration stage followed, with enthusiasm about AI transforming industries and society surging. However, concerns about misinformation, job loss, bias, and misuse began to be amplified. As we move into the Panic/Backlash stage, governments, media, and the public express fears about AI safety, ethical risks, and societal disruption, sparking calls for regulation and moratoriums.
Despite these concerns, efforts are underway to develop AI governance, ethical standards, and a better understanding of the technology. This suggests we may be moving toward more measured integration, marking the Resolution/Normalization stage.
The current generative AI panic is a prime example of the Panic/Backlash stage of the Tech Panic Cycle, characterised by widespread anxiety and increased scrutiny, which will likely be followed by a phase of adaptation and normalization as society learns to manage the technology responsibly.
The Tech Panic Cycle is influenced by four elements: elitism, legacy industries, anti-tech crusaders, and news media. To navigate this cycle effectively, policymakers are advised to recognise when a tech panic is happening and exercise caution when addressing hypothetical or exaggerated concerns about generative AI.
Moreover, the report urges policymakers to avoid overreacting to nascent fears when formulating policy to prevent undue harm to generative AI through misguided laws and regulations. The report emphasises that the current generative AI panic is part of a long series of tech panics, including many in the creative sector.
To illustrate this point, the report presents three historical case studies of tech panics: the printing press, phonograph, and photography innovations. The report outlines a historical pattern of technology panics, tracing it from the advent of the printing press to the present day.
The report advises against rushing to regulate AI before others do, as this could lead to missed opportunities for society. As the public embraces the new tool, and it becomes clear that many fears will never materialize, we enter the Deflating Fears stage.
In conclusion, the current panic over generative AI can be better understood through the lens of the Tech Panic Cycle. Recognising this cycle and its stages can help policymakers navigate the current situation and make informed decisions about the future of AI.
- The Centre for Data Innovation's report on generative artificial intelligence (AI) highlights a pattern called the Tech Panic Cycle, likening it to market or moral panics, technology hype cycles, and the Discovery/Introduction stage of the cycle has already been reached with the emergence of AI models like GPT.
- As we progress through the Hype and Exaggeration stage of the Tech Panic Cycle, enthusiasm for AI renovating industries and society escalates, yet apprehensions about misinformation, job loss, bias, and misuse increase correspondingly.
- The ensuing Panic/Backlash stage elicits concerns about AI safety, ethical risks, and societal disruption, leading to calls for regulation and moratoriums in policy-and-legislation.
- To avoid overreacting, the report counsels policymakers to be mindful when addressing potential concerns regarding generative AI, and to take care in resolving misguided laws and regulations stemming from the Tech Panic Cycle.
- To grasp the persisting nature of tech panics, the report offers three historical examples: the printing press, the phonograph, and photography, demonstrating that these panics have repeating patterns throughout general-news, lasting from their inceptions to the present day.
