Improvements to a number of Apple services - including a more personalised version of its virtual assistant, Siri - are to be powered with AI provided by Google. The tech giants have announced a multi-year collaboration which will see the iPhone-maker base some of its key tech on Google's Gemini AI models. In a joint statement, the two firms said the partnership would unlock innovative new experiences for Apple users. However, experts say it demonstrates how Apple's cautious approach to building and rolling out its own AI tools has left it reliant on other companies. By outsourcing the foundational layer of its AI to Google, Apple is effectively admitting that its internal efforts couldn't compete with Google's Gemini in terms of capability and scale in the short term, IDC analyst Francisco Jeronimo said.

Welcome to Big Tech's'Age of Extraction' In his new book, antitrust scholar and former White House adviser Tim Wu argues that tech giants are bleeding you dry--and lays out a plan to stop them. Growing up in Toronto, Tim Wu had a classmate who was the progeny of Communist parents. His name was Cory Doctorow. Yes, the same guy who just published a book about enshittification . Though they shared a general world view, the boyhood pals also had arguments, with Wu typically taking a less radical stance than his buddy.

Typical measures of market power in economic theory focus on classical pricing markets of homogeneous goods, where a firm's primary action is choosing a price to sell the good or the quantity of This simple relationship allows one to directly reason about participant welfare and profit of firms. In addition, not all participants with accounts on a digital platform are equally active and inactive participants should not factor into the market power of a firm the same way active participants do. Participant behavior plays a critical role in digital market places. As outlined by the Stigler Committee [2019], "the findings from behavioral economics demonstrate an under-recognized market power held Thaler and Sunstein, 2008; Fogg, 2002]--can be exploited by firms in digital economies, but do not factor into traditional measures of market power. Performative power focuses on measuring power rather than harm.

Just six major technology companies are at the heart of the AI sector through an "interconnected web" of more than 90 investments and partnerships links, the UK's competition regulator has warned, sparking increased concern about the anti-competitive nature of the technology. Sarah Cardell, the chief executive of the Competition and Markets Authority, said AI foundation models – general-purpose AI systems such as OpenAI's GPT-4 and Google's Gemini, on which consumer and business products are frequently built – were a potential "paradigm shift" for society. Speaking in Washington, she added that the immense concentration of power they represented would give a small number of companies "the ability and incentives to shape these markets in their own interests". "When we started this work, we were curious. Now, with a deeper understanding and having watched developments very closely, we have real concerns," Cardell said.

A report published this week by the U.K.'s Competition & Markets Authority (CMA) has raised concerns about the potential ways the artificial intelligence industry could become monopolized or harm consumers in future, but stressed that it is too soon to tell whether these scenarios would materialize. The issues raised by the report highlight the difficulties policymakers face in governing AI, a source of both huge potential commercial value and many risks. Rishi Sunak, the British Prime Minister, is pushing for the U.K. to occupy a central role in international AI policy discussions, with a particular focus on risks from advanced AI systems. If the U.K. competition watchdog decides to start taking action against AI developers, tech companies around the world could be affected. The report, published on Monday, focuses on foundation models, which the CMA defines as "a type of AI technology that are trained on vast amounts of data that can be adapted to a wide range of tasks and operations." Examples include text-generating AI models, such as GPT-3.5, the model that powers OpenAI's ChatGPT, as well as image-generating AI models, such as Stable Diffusion.

People should not assume a positive outcome from the artificial intelligence boom, the UK's competition watchdog has warned, citing risks including a proliferation of false information, fraud and fake reviews as well as high prices for using the technology. The Competition and Markets Authority said people and businesses could benefit from a new generation of AI systems but dominance by entrenched players and flouting of consumer protection law posed a number of potential threats. The CMA made the warning in an initial review of foundation models, the technology that underpins AI tools such as the ChatGPT chatbot and image generators such as Stable Diffusion. The emergence of ChatGPT in particular has triggered a debate over the impact of generative AI – a catch-all term for tools that produce convincing text, image and voice outputs from typed human prompts – on the economy by eliminating white-collar jobs in areas such as law, IT and the media, as well as the potential for mass-producing disinformation targeting voters and consumers. The CMA chief executive, Sarah Cardell, said the speed at which AI was becoming a part of everyday life for people and businesses was "dramatic", with the potential for making millions of everyday tasks easier as well as boosting productivity – a measure of economic efficiency, or the amount of output generated by a worker for each hour worked.

We introduce the notion of performative power, which measures the ability of a firm operating an algorithmic system, such as a digital content recommendation platform, to cause change in a population of participants. We relate performative power to the economic study of competition in digital economies. Traditional economic concepts struggle with identifying anti-competitive patterns in digital platforms not least due to the complexity of market definition. In contrast, performative power is a causal notion that is identifiable with minimal knowledge of the market, its internals, participants, products, or prices. Low performative power implies that a firm can do no better than to optimize their objective on current data. In contrast, firms of high performative power stand to benefit from steering the population towards more profitable behavior. We confirm in a simple theoretical model that monopolies maximize performative power. A firm's ability to personalize increases performative power, while competition and outside options decrease performative power. On the empirical side, we propose an observational causal design to identify performative power from discontinuities in how digital platforms display content. This allows to repurpose causal effects from various studies about digital platforms as lower bounds on performative power. Finally, we speculate about the role that performative power might play in competition policy and antitrust enforcement in digital marketplaces.

Decentralized electricity markets are often dominated by a small set of generator companies who control the majority of the capacity. In this paper, we explore the effect of the total controlled electricity capacity by a single, or group, of generator companies can have on the average electricity price. We demonstrate this through the use of ElecSim, a simulation of a country-wide energy market. We develop a strategic agent, representing a generation company, which uses a deep deterministic policy gradient reinforcement learning algorithm to bid in a uniform pricing electricity market. A uniform pricing market is one where all players are paid the highest accepted price. ElecSim is parameterized to the United Kingdom for the year 2018. This work can help inform policy on how to best regulate a market to ensure that the price of electricity remains competitive. We find that capacity has an impact on the average electricity price in a single year. If any single generator company, or a collaborating group of generator companies, control more than ${\sim}$11$\%$ of generation capacity and bid strategically, prices begin to increase by ${\sim}$25$\%$. The value of ${\sim}$25\% and ${\sim}$11\% may vary between market structures and countries. For instance, different load profiles may favour a particular type of generator or a different distribution of generation capacity. Once the capacity controlled by a generator company, which bids strategically, is higher than ${\sim}$35\%, prices increase exponentially. We observe that the use of a market cap of approximately double the average market price has the effect of significantly decreasing this effect and maintaining a competitive market. A fair and competitive electricity market provides value to consumers and enables a more competitive economy through the utilisation of electricity by both industry and consumers.

The UK's Competition and Markets Authority (CMA) has called on the UK government to create "a new pro-competition regulatory regime" that can control Facebook, Google and other technology companies that are primarily funded by digital advertising. The non-ministerial department has completed a study announced last July and concluded that "existing laws are not suitable for effective regulation." To combat the problem, it's recommending that a new Digital Markets Unit be set up with major oversight and powers. The Unit was first proposed in a report published by the Digital Competition Expert Panel (DCEP) -- a group chaired by Professor Jason Furman, a former chief economist when Barack Obama was president -- in March 2019. The CMA believes it should have a code of conduct that ensures Facebook and Google don't veer into "exploitative or exclusionary practices," or do anything that is likely to reduce public trust and transparency.