{"id":2177,"date":"2024-05-16T21:04:39","date_gmt":"2024-05-16T19:04:39","guid":{"rendered":"https:\/\/www.rivistaeco.com\/?p=2177"},"modified":"2024-05-27T18:04:17","modified_gmt":"2024-05-27T16:04:17","slug":"who-is-afraid-of-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/www.rivistaeco.com\/en\/2024\/05\/16\/who-is-afraid-of-artificial-intelligence\/","title":{"rendered":"Who is afraid of artificial intelligence?"},"content":{"rendered":"

Europe is often at the forefront of regulating digital technologies, and it continues to be so with the enactment of the Artificial Intelligence Act. This is a crucial step in establishing rules for a technology that promise significant innovations but also carries risks that are not always apparent.<\/span><\/i><\/p>\n

Artificial intelligence (AI) is the technology of the moment. On 30 November 2022, ChatGPT was launched: a generative AI model, or an algorithm that enables the generation of content (initially text only) that is coherent, well-written, and capable of fulfilling nearly every user request. Since then, other generative AI algorithms have been introduced to the public, not only for writing text but also for generating images, audio, and videos, and even creating and modifying programming codes underpinning any type of software. The tasks to which AI is applied are growing daily, making AI omnipresent in our lives \u2013 in newspaper headlines, discussions on social networks, companies, and universities.<\/span><\/p>\n

The AI Already Among Us<\/b><\/h3>\n

Generative AI models like ChatGPT are the most well known to the general public, but AI takes many forms. Companies have been using AI algorithms for years to influence our consumption and spending, often without our realizing it. For example, in some countries, gas stations set fuel prices using algorithms that continuously analyse consumer demand and competitors\u2019 prices. In principle, the work of the algorithm is similar to what a human would do: it observes the prices of nearby distributors, measures the demand for fuel over a certain period, and adjusts the price accordingly.\u00a0<\/span><\/p>\n

However, AI behaviour differs significantly from a human operator in three ways: the high frequency with which it can change prices, the number of price changes made, and the rapidity of response to those of nearby stations. AI can perform these operations with a speed and precision infinitely superior to that of a human, allowing distributors to increase their profits. The process is also very different: while a human relies on their experience and common sense and tries to make the best choice within constraints they believe should be respected, the algorithm learns through trial and error, experimenting with what happens to what it wants to optimize (e.g., revenue) as it tests different prices. This can lead to pricing strategies very different from those we would observe if prices were determined by humans.<\/span><\/p>\n

AI forms are already used in other areas relevant to consumers. In the summer of 2023, there was much discussion over how using AI to set airfare rates made price hikes more marked, frequent, and personalized, always reflecting the peaks of demand for flights to Sicily and Sardinia. Recommendation systems are also types of AI: algorithms predict a user\u2019s potential interest in items they have not yet experienced. Social media platforms use them to populate user feeds, Spotify to generate playlists, YouTube and Netflix to recommend videos, and Google Scholar to suggest studies for academics to read. Financial institutions employ them for investor products (\u201crobo-advisors\u201d). Employment agencies match workers and employers. These personalized predictions are based on user feedback, such as ratings, clicks, or other online activity that, once collected and categorized, become the input for algorithms to generate recommendations.<\/span><\/p>\n

Furthermore, as some research has highlighted, the way algorithms learn from their past actions can lead them to adopt cooperative behaviors. Algorithms from rival companies in the same market can learn to choose strategies like a cartel, agreeing to limit competition and set prices higher than those of a fully competitive environment. This is referred to as algorithmic collusion. A study on German gas stations showed how the widespread use of AI had increased their profits by up to 38%, a staggering increase. The profit growth was mainly due to price increases for consumers.<\/span><\/p>\n

AI has already radically changed a large number of markets. Online advertising, for example, which is a financial engine for the technology economy, would be very different without AI. Even without considering the latest innovations \u2013 such as the decision of Meta (the company that owns Facebook) to make generative AI available to companies to personalize advertisements targeting individual users \u2013 this market has long entrusted algorithms with decisions for key operations.\u00a0<\/span><\/p>\n

For example, the main market for online advertising is associated with search engines: when we query Google or other engines, some of the links that appear \u2013 those at the top or bottom of the page marked \u201csponsored\u201d \u2013 are advertisements. These advertising spaces have great value because they are highly targeted, meaning the advertisement is directed toward users searching specific keywords. Typically, the advertiser has many options to further define their targets.\u00a0<\/span><\/p>\n

But precise targeting requires the processing of a large amount of data, as does optimizing the price to offer in auctions for the virtual advertising spaces. The result is that AI algorithms choose most of the advertisements we are exposed to every day and thus determine the trends of a market that, according to Statista (a website that processes and publishes statistics), will exceed 300 billion US dollars in 2024.<\/span><\/p>\n

Not surprisingly, the online advertising sector is defined as a \u201ccore\u201d service under the recent EU regulatory intervention the Digital Markets Act, which became fully operational in early March 2024.<\/span><\/p>\n

Artificial Intelligence and the \u201cBrussels Effect\u201d<\/b><\/h3>\n

Europe, consistently at the forefront of regulating digital technologies, continues to lead with the AI Act. This regulation not only deals with a technology that will significantly alter our way of life but also already affects the investment choices of advanced companies and governments. By proactively establishing new market rules, the EU can compel businesses \u2013 especially American tech giants \u2013 to adhere to European laws, even outside the Union. This is often called the \u201cBrussels Effect.\u201d<\/span><\/p>\n

On 23 April 2024, the Council of Ministers approved the draft law on AI that the Italian government has been developing, following the European Parliament\u2019s passing of the AI Act. This legislation is part of a complex legal landscape that affects many aspects of AI, impacting both tech companies and consumers. At the time of writing, there are at least thirteen other regulatory packages concerning digital matters.<\/span><\/p>\n

Rules, But Without Stifling the System<\/b><\/h3>\n

The growing number of European laws on digital markets could pose a risk to technology companies\u2019 investments in Europe. The multitude of legislative packages often overlap, making it difficult for companies to interpret them. For instance, MedTech Europe, the European association of medical device manufacturers, has complained that many products are subject to the overlapping rules of three legislative packages: the AI Act, Medical Devices Regulation, and In Vitro Medical Devices Regulation. Without standardizing the rules, legal uncertainties and bureaucratic complexities could delay the introduction of significant medical innovations into the European market.<\/span><\/p>\n

Nonetheless, the benefits of European regulations are undeniable. While simplifying the regulatory corpus concerning AI is desirable, the existence of these norms itself represents a considerable effort toward uniformity. European legislation reduces the need for individual member states to enact national laws, which could vary greatly from one country to another. Without European standards, we would see a proliferation of local laws, leading to an extremely fragmented European legislative framework and more complexity for companies to comply. Thus, even with a focus on simplification, European regulations are a step forward.<\/span><\/p>\n

Obvious and Hidden Risks<\/b><\/h3>\n

But simplification and uniformity are not the only positive effects of establishing European standards. European regulations are also necessary to mitigate the risks associated with a technology like AI, which, if unregulated, could pose dangers to individuals, the economy, and society at large. Some risks are obvious and objective, which is why the AI Act prohibits certain types of AI \u2013 for example, the use of AI algorithms to evaluate people based on behaviour or personal characteristics (known as social scoring), as well as techniques aimed at manipulating human behaviour. Similarly, algorithms intended for recognition of feelings at the workplace and in schools and biometric categorization to infer sensitive data, such as sexual orientation or religious beliefs, are banned.\u00a0<\/span><\/p>\n

Other risks are subtler but just as real, such as those involving algorithms that determine pricing and learn to collude, consequently charging consumers higher prices. Detecting such risks is challenging and requires constant vigilance from legislators and researchers, who will need to update the legislation as new risks emerge. For example, the Italian government has already granted new powers to the Competition and Market Authority to address the negative effects that pricing algorithms might have on the airline fare market and consumers.<\/span><\/p>\n

While some of AI\u2019s risks and benefits are currently clear, future risks and benefits will depend on how the technology evolves in the coming months and years. In conclusion, European regulations and their continuous update are a necessary evil. While they may pose difficulties for businesses and discourage some investments within the Union, they are effective in defining a common framework for member states and are essential for protecting citizens, the market, and society.<\/span><\/p>\n

Francesco Decarolis<\/strong> is a Full Professor of economics at Bocconi University in Milan. He has served as an expert for the European Commission on digitalization and competition.<\/span><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

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