AI Addiction Sparks Debate Over Corporate Responsibility and Regulation

If AI is addictive, where does the responsibility lie - with big tech or its users?

When I talk to my son, an engineering student, and we have a question or disagreement, he immediately turns to ChatGPT as his primary source of information and confirmation. He is not alone in this. The use of generative AI tools has exploded across different demographic groups. For many people, these tools can be entertaining, informative and beneficial. However, they also have a dark side. Generative AI is not formally recognised as addictive right now - the medical evidence is still being gathered. But there is a significant amount of data showing heavy use of chatbots and other systems that produce text, images and video leads to neural patterns and behaviour that are associated with addiction. In light of Meta's and YouTube's recent legal defeat in a landmark social media addiction trial, I believe it's time to ask whether a similar logic applies to generative AI - and how it could be addressed. The starting point would be to identify who carries responsibility for overuse of generative AI. The science on this is not settled, and there are some who counsel caution when using the term addiction. They propose the use of other expressions such as "problematic use". However, in a recent paper, our team of researchers suggest there is strong evidence to suggest that generative AI has addictive properties. Much-discussed examples include emotional dependency on chatbot companions, compulsive engagement with them, and the loss of real-world acquaintances and friends. A key factor here is that, as in all cases of addiction, the behaviour has negative consequences for the user which may affect both their personal and professional lives. If we follow the argument that generative AI is a candidate for addictive behaviour, then we also need to look at responsibility. Societies tend to find ways to deal with harm by holding people or groups responsible for fixing it. Those who could be accountable include legislators, regulators, industry and health systems. Historical examples Historical precedents such as smoking might offer insights into how the area of generative AI addiction could evolve. Older readers may remember when the Marlboro Man would appear before any feature movie in their local cinemas. It eventually transpired that not only was smoking addictive and bad for your health, but that tobacco companies knew this. Nevertheless, it was publicly denied. This led to lengthy and high-profile litigation, eventually resulting in large-scale financial payouts and changes to the industry. These changes included the plain packaging of tobacco products and gruesome warning labels on them. Gambling could be following a similar trajectory - and now social media companies may be taking their first steps into a similar process. A key question is whether the makers of a product - be it tobacco, gambling or social media - are aware of its addictive properties. Another important factor being considered is whether certain companies may even use the allegedly addictive properties of their products for corporate advantage. AI is not tobacco, of course, but there may be parallels to be studied. In our research, we have identified four groups of stakeholders that are now being called upon to address the challenges linked to the possibility of addiction to generative AI. The first is governments and regulators. These have a key role to play in highlighting the problems, setting the rules of engagement, and creating incentives for other parties to engage with the topic. They can do this by requiring labelling, restricting advertising, applying liability law and providing research funding - along with many other mechanisms. But the most important role in addressing potential addictive behaviour associated with generative AI would be held by big tech companies that develop and own these technologies - and stand to benefit financially from them. These companies own and have access to user data, which would be needed to ascertain the features that support or alleviate addiction. They are also the parties that would benefit financially from addiction by increasing user numbers and engagement, the main currency of the digital age. In addition to these two groups, academic researchers have an important role in collecting and interpreting data, and providing the evidence needed to recognise addiction and addictive features - in ways that allow for evidence-based political or legal debate. Finally, civil society organisations such as user or patient groups can help by providing support, advocating for members' interests, and establishing early-warning structures. The point is that none of these interested parties can address the problem on their own. They need to collaborate. Someone else's problem A key problem at the moment is the lack of structured debate about responsibilities - everybody assumes it is someone else's problem. But there is ample precedent showing how greater engagement from those involved with the issue may be achieved. With tobacco, the World Health Organization (WHO) formed the Framework Convention on Tobacco Control - a treaty-based mechanism that brought together governments, public health bodies, researchers and civil society to evaluate evidence and draw up common rules. The International AI Safety Report shows comparable international consensus-building activities are already happening in other aspects of AI. Some responsibility also falls on the users of AI, who should try to avoid or control their own potentially harmful behaviour. But appeals to individual moderation or mindfulness have been shown with other addictions to be insufficient. While the harms associated with smoking or alcohol misuse are well known, society still relies on age limits, packaging rules and advertising restrictions. Generative AI is being integrated into the everyday fabric of our society. The choices we now make will determine what acceptable use looks like for years to come.

'Regulation by litigation is often overlooked as a regulatory tool': Just how much responsibility should AI companies have on their users' wellbeing?

Should courts treat addictive AI companion features as product defects? Artificial intelligence has become far more than just a productivity aid - for many, it's now a friend, mentor and therapist. Millions of users now interact with chatbots daily, with tools capable of remembering past conversations and adapting to personal context. With that in mind, a growing debate is now emerging around whether AI is being designed to help users, or whether it's actually being built to keep them engaged for as long as possible. And it's a concern that's oh so familiar, with similar worries already raised about social media platforms. Infinite scrolling and algorithmic recommendations have already kept millions hooked, and now, critics argue AI companions may be doing exactly the same thing. Recent reports have emerged linking AI companion use to emotional dependency, poor mental health and, in some of the rarest cases, more tragic outcomes. Dr Ayelet Gordon-Tapiero from the Benin School of Computer Science and Engineering at the Hebrew University of Jerusalem believes that AI products should be treated just like any other consumer products - rather than seeing emotional dependency, addiction and manipulative behavior as unfortunate side effects, she suggests courts may eventually need to consider whether those outcomes are actually product defects, which could expose developers to legal liability. But this begs the question of how much responsibility companies should bear for the emotional wellbeing of users, and how regulation could shape that responsibility. To better understand these side effects, I spoke with Gordon-Tapiero about the psychology behind AI addition, how it compares to social media and the role of regulation. * In one of our email exchanges, you agreed that AI friends could become as addictive as drugs. Could you expand that further? The design of AI companions reflects the result of decades of research in the fields of Human-Computer-Interaction (HCI) and Human-Robot-Interaction (HRI). Researchers in these fields spent years finding ways, through experimentation, to make computer systems more appealing, engaging and empathetic. These design choices have been successful in eliciting addictive responses from users. In terms of the outcome of such addiction, unfortunately we are already seeing numerous cases of harms stemming from the use of AI companions - a feedback loop where users turn to AI companions to help them deal with anxiety and depression but end up exacerbating these conditions, children who spend hours and hours interacting with their AI companion instead of playing outdoors, interacting with friends or even sleeping. Every few weeks we read about cases of children taking their lives after prolonged 'relationships' with AI companions. These concerns are likely to increase as AI companions gain popularity, particularly with children and other vulnerable individuals. * It's not just the small players though. Internal documents from Microsoft reveal plans to "make people addicted" to its new AI assistant, so is it just the playbook, the usual MO of everything in our world that goes viral? It is tempting to view AI companions as a new phenomenon, perhaps part of the larger trend of AI-doomerism. I would resist this framing. Instead, I see a direct line connecting the purposely addictive nature of social media to the harms we are encountering in the use of AI companions. The same financial incentives seem to drive the design of both types of technology. What is different is the type of interaction - whereas social media facilitated interactions with other users, AI companions create a technological bubble with only one human actor. * All this is driven by cold capitalism though. The drive for efficiency, maximizing ARPU and usage. That's what gave rise to infinite scrolls and short form videos. That is not intrinsically bad. How can this sort of behaviour be discouraged without impacting the bottom line. It is true that maximizing profits is not intrinsically bad. At the same time, as a society we do not believe that profit maximization is the only goal that should be promoted or protected. In certain settings we may limit profit maximization to promote other interests - particularly where vulnerable individuals are concerned. For example, we limit advertising and selling cigarettes to children even though such sales could drive revenue for tobacco companies. We even have a common-law legal doctrine that is particularly aimed at dealing with cases in which we believe that the enrichment by a corporation comes at the expense of individuals and allows us, under certain circumstances, to disgorge the profits generated unjustly. The challenge is identifying when corporate practices cross the line of legitimate profit maximizing. * I am sceptical about your call to regulate by litigation. Other than US, the rest of the world seems to be less inclined to use courts in that manner. Don't you think so? Regulation by litigation is often overlooked as a regulatory tool. In the context of technology, it offers a nimbleness that command-and-control regulation simply cannot keep up with. Regulation by litigation is an approach used in many fields in common law countries, such as the United Kingdom. One of the tools that common law litigation offers are broad doctrinal categories that are flexible and can be applied and adapted by courts in particular settings. As I mentioned in the previous question, the doctrine of unjust enrichment is one such tool, and products liability is another one. For example, the question of whether software is a product was recently discussed in an American court litigating an AI companion case. In Garcia v. Character Technologies, the Court ruled that AI companions should be viewed as a product, allowing plaintiffs to sue based on products liability. The question of whether software should be treated as a product, which is clearly defined in the EU through a directive, was shaped in the US by a court. * Is it too late to change the way things are done? Is regulation useless as the market is moving so fast? What else can be done? It is not too late, but the more we wait the harder it will be to make meaningful structural changes to technology. Regulation is not useless, but neither is it a panacea. Thus, while regulation can and should set important boundaries, we should solely rely on it, nor should we wait for it idly. Instead, education is still the most important tool we have. Teaching adults and children about the promise and perils of technology, AI and AI companions has the power to incentivize the most change in the companies developing these tools. If we refuse to use technology that is harmful for us, if we demand technology that encourages deliberation and brings humans closer together, the benefits will extend beyond the bottom line of companies to individuals and society at large. Follow TechRadar on Google News and add us as a preferred source to get our expert news, reviews, and opinion in your feeds.