The Promise (and Dangers) of the Data Revolution

Emma Weibel
5 days ago
5 min read

Various speakers at the Warwick Economics Summit 2026

This article is written by Emma Weibel, a WES 2026 student journalist and writer for The Sundial Press.

The 25th edition of the Warwick Economics Summit took place in a time of change and turmoil worldwide. During the conference, amidst discussions of journalism, business, urban development, and conflict, one talking point remained constant: the data revolution. Data is the raw material of the future, and thus the question at the forefront is how to harness data to its greatest extent using new artificial intelligence tools. At the same time, discourse focused on the possible implications of this technology for the present and the future, with diverging visions among different speakers about whether the data revolution spells prosperity or disaster.

The conference kicked off with a keynote by Financial Times CEO Jon Slade titled “Building the Market for Truth: AI, Economics, and Democracy,” opening this discussion quite directly. Slade’s talk delivered a troubling diagnosis of the degradation of our shared sense of truth as a result of the flood of unchecked AI-generated content. As he puts it, trust is the invisible infrastructure that holds journalism (and society) together; without it, we risk that it all comes tumbling down. The problem, he says, is the non-consensual extractive process utilized by data giants to train AI models on human journalism with no regulation. Not only does this infringe on the rights of journalists, but it also results in a massive flow of unattributable and often incorrect information. His vision, however, is not to block AI companies from accessing information from traditional media outlets. Rather, it is to create an economic flywheel based on a consensual relationship that is mutually beneficial and safeguards the quality of media. The AI industry has no problem paying large sums for the best technology and engineers, so why shouldn’t it be the same for what is perhaps the most integral part of AI systems: data? For Slade, a successful partnership would be built on transparency, attribution, and choice: journalistic platforms license the use of their information to data companies who, in turn, offer transparent outputs to their consumers with attributions. This approach works, he argues: the Financial Times was the first media company to license all of its archives to OpenAI, which has resulted in ChatGPT generating more accurate information about the media company’s content. While the FT CEO believes the mutual benefits of this agreement serve as a significant incentive for data companies to agree, he also concedes that regulation will be necessary. In particular, existing copyright laws need to be enforced to ensure that journalists get credit and compensation for the use of their content. Further, when asked about rising concerns about the environmental impact of AI infrastructure, he said that increasing transparency regarding emissions data could also be a part of these business agreements. His vision for the future of the data revolution, thus, is a cautious but optimistic one, based on the idea that partnership and transparency can help salvage the quality of media. He makes clear that, unchecked, these new tools–no matter how efficient they make accessing information–can have disastrous effects: “technology will constantly tempt you to move faster, automate more, and remove friction wherever you find it.” “Friction is where judgment lives, so be careful which friction you remove.”

This perspective stood in contrast with that of the next keynote speaker and the CFO of Nestlé: Anna Manz. In a very metrics-driven talk, Manz broke down her role in ensuring Nestlé’s continued competitiveness and supremacy of the markets. Throughout her talk, she placed great emphasis on the potential of automating the analysis of data. Unleashing the data could, in her opinion, help the company deal with supply chain shocks and avoid possible malpractice by being able to keep track of all the diverse factors involved in running such a massive international company. The Nestlé CFO’s vision was quite different from Mr. Slade’s earlier that day: for her, the interactions between consumers and producers should be crunched down into hard numbers so as to minimize friction and maximize profits. The future of business lies in embracing artificial intelligence to tap into the power of this data.

But is there a risk in treating people as data points? The Executive Director of UN-Habitat, Anacláudia Rossbach’s keynote on the second day of the conference seems to imply just that. As the head of the United Nations’ urbanization and sustainable development wing, Rossbach is tasked with addressing the needs of more than 3 billion people worldwide who lack adequate housing. With such a global operation, one might expect her to take a similar approach to Ms. Manz. While during a small-group “meet the speaker” session, the UN-Habitat director underlined the need for more robust data in development, especially in the Global South, her overall message was a very different one. Her vision rejected the more top-down approach, arguing that high-level metrics such as GDP cannot be the unique measure of success. Instead, we must focus “on improving the quality of life of the population beyond the GDP,” prioritizing the needs of communities over macro-outputs because “how can we achieve the SDGs [Sustainable Development Goals] as a whole if people don’t have a roof over their heads?” This all comes back to the core characteristics of the data revolution and its implications on the sense of connection between individuals and communities. It calls for a middle ground between impersonal action from behind a computer screen and the deeply personal action that happens on the ground, face-to-face. Can shared trust be built on profit-maximizing algorithms? Will “unleashing the data” ensure a better quality of life for the world’s most marginalized? Rossbach dares us to consider that the key to a better future may not be more data connection, but deeper interpersonal connection.

This discussion is neatly wrapped up by a powerful talk by Ukrainian Nobel Prize Laureate Oleksandra Matviichuk on the final day of the conference. Particularly interesting to the topic of the digital era is her characterization of the divisions sown by authoritarianism. Her words echo those of Jon Slade two days earlier, warning of the way digital media threatens our shared sense of reality and makes us vulnerable to external manipulation. While the theme of data was not at the center of her talk, it is an important factor (and weapon) in contemporary war. The Nobel Prize Laureate stressed the agency and strength of ordinary people when the macro-systems meant to ensure their protection fail; in this, she also evokes Anacláudia Rossbach’s call for a bottom-up approach to justice.

At this point, the topic of artificial intelligence technology cannot be avoided in a discussion about the future of our society. Inevitably, there are diverging perspectives among the leaders of today and those of tomorrow on the practical and moral implications of the data revolution. Perhaps there is a future where transparency and trust prevail in the data industry, or (more likely) one where data analysis tools revolutionize the way business is conducted. Certainly, the lives of people living in wealthy, developed nations will be simplified by these technologies–but at what cost? Discussions of this uncertain future took center stage at WES this year, a preview of the debates on the promise and dangers of the data revolution that will play out in the years to come.

The views and opinions expressed in this article belong solely to the writer and do not necessarily reflect the views and opinions of the Warwick Economics Summit.

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