Is competition in the digital economy desirable? Does it currently exist? Is it possible? Is there anything policy can do?

This talk addresses all of these questions and presents the recommendations of the Digital Competition Expert Panel which was chaired by Jason Furman and recently presented its recommendations to the government.

The 5th Annual Oxford Business and Poverty Conference will feature a diverse range of speakers addressing the Paradoxes of Prosperity. Sign up here: https://www.eventbrite.com/e/5th-annual-oxford-business-poverty-conference-tickets-57733957822
Hosted at the Sheldonian Theatre, the conference will feature keynotes by:
Lant Pritchett: RISE Research Director at the Blavatnik School of Government, former Senior Fellow at the Center for Global Development
Efosa Ojomo: Global Prosperity Lead and Senior Researcher at the Clayton Christensen Institute
John Hoffmire: Director of Center on Business and Poverty and Research Associate at Kellogg Colleges at Center For Mutual and Employee-owned Business at Oxford University
Ananth Pai: Executive Director, Bharath Beedi Works Pvt. Ltd. and Director, Bharath Auto Cars Pvt
Laurel Stanfield: Assistant Professor of Marketing at Bentley College in Massachusetts
Grace Cheng: Greater China’s Country Manager for Russell Reynolds Associates
Madhusudan Jagadish: 2016 Graduate MBA, Said Business School, University of Oxford
Tentative Schedule:
2:15-2:20 Welcome
2:20-2:50 Efosa Ojomo, co-author of The Prosperity Paradox, sets the stage for the need for innovation in development
2:50-3:20 John Hoffmire, Ananth Pai and Mudhusudan Jagadish explain how the Prosperity Paradox can be used in India as a model to create good jobs for poor women
3:20-3:40 Break
3:40-4:10 Laurel Steinfeld speaks to issues of gender, development and business – addressing paradoxes related to prosperity
4:10-4:40 Grace Cheng, speaks about the history of China’s use of disruptive innovations to develop its economy
4:40-5:15 Break
5:15-6 Lant Pritchett talks on Pushing Past Poverty: Paths to Prosperity
6:30-8 Dinner at the Rhodes House – Purchase tickets after signing up for the conference
Sponsors include: Russell Reynolds, Employee Ownership Foundation, Ananth Pai Foundation and others

Data-driven micro-targeted campaigns have become a main stable of political strategy. As personal and societal data becomes more accessible, we need to understand how it can be used and mis-used in political campaigns and whether it is relevant to regulate political candidates’ access to data.

This book talk will be followed by a drinks reception and book sale, all welcome

Big data and AI are starting to feature in cancer research today, and will will play an even greater role in the future. Join researchers from Cancer Research UK to discover the technologies and methods they use to help find, prevent and treat cancer, and what big ideas they have for the future.

IF Oxford is operating a Pay What You Decide (PWYD) ticketing system. This works by enabling you to pre-book events without paying for a ticket beforehand. Afterwards, you have the opportunity to pay what you decide you want to, or can afford. If you prefer, you can make a donation to IF Oxford when you book. All funds raised go towards next year’s Festival.

Geographers have long been interested in the spaces brought into being by the internet. In the early days of the Web, digital technologies were seen as tools that could bring a heterotopic cyberspace into being: a place beyond space de-tethered from the material world.

More recent framings instead see digital geographies as always-augmented, hybrid, and ontogenetic: integrally embedded into everyday life.

Against that backdrop, Professor Mark Graham will present findings from three large research projects about digital platforms. First, a large-scale digital mapping project that looks at how digital inequalities can become infused into our urban landscapes. Second, a study about the livelihoods of platform workers in Southeast Asia and Sub-Saharan Africa. Finally, early results from a new action research project (the Fairwork Foundation) designed to improve the quality of platform jobs.

In each case, the talk explores why understanding the ways that platforms command digital geographies is a crucial prerequisite for envisioning more equitable digital futures.

Please register via the link provided. This talk will be followed by a drinks reception, all welcome.

Charles Babbage has been called the ‘great-uncle’ of modern computing, a claim that rests simultaneously on his demonstrable understanding of most of the architectural principles underlying the modern computer,band the almost universal ignorance of Babbage’s work before 1970. There has since been an explosion of interest both in Babbage’s devices and the impact they might have had in some parallel history, and in Babbage himself as a man of great originality who had essentially no influence at all on subsequent technological development.

In all this, one fundamental question has been largely ignored: how is it that one individual working alone could have synthesised a workable computer design over a short period, designing an object whose complexity of behaviour so far exceeded that of contemporary machines that it would not be matched for over one hundred years?

Our Leverhulme funded project Notions and notations: Charles Babbage’s language of thought investigated the design methods that Babbage used, and their impact on subsequent design practice. As part of that work we constructed a steam-driven difference engine to Babbage’s outline design.

In this general interest talk, we shall describe some aspects of Babbage’s designs and design methods, and demonstrate the difference engine.

This talk will describe a class of machine learning methods for reasoning about complex physical systems. The key insight is that many systems can be represented as graphs with nodes connected by edges. I’ll present a series of studies which use graph neural networks–deep neural networks that approximate functions on graphs via learned message-passing-like operations– to predict the movement of bodies in particle systems, infer hidden physical properties, control simulated robotic systems, and build physical structures. These methods are not specific to physics, however, and I’ll show how we and others have applied them to broader problem domains with rich underlying structure.

In modern high-tech health care, patients appear to be the stumbling block.

Uninformed, anxious, noncompliant individuals with unhealthy lifestyles who demand treatments advertised by celebrities and insist on unnecessary but expensive diagnostics may eventually turn into plaintiffs. But what about their physicians? About ten years ago, Muir Gray and Gerd Gigerenzer published a book with the subtitle “Envisioning health care 2020”. They listed “seven sins” of health care systems then, one of which was health professionals’ stunning lack of risk literacy. Many were not exactly sure what a false-positive rate was, or what overdiagnosis and survival rates mean, and they were unable to evaluate articles in their own field. As a consequence, the ideals of informed consent and shared decision-making remain a pipedream – both doctors and patients are habitually misled by biased information in health brochures and advertisements. At the same time, the risk literacy problem is one of the few in health care that actually have a known solution. A quick cure is to teach efficient risk communication that fosters transparency as opposed to confusion, both in medical school and in CME. It can be done with 4th graders, so it should work with doctors, too.

Now, in 2020, can every doctor understand health statistics? In this talk, Gerd Gigerenzer will describe the efforts towards this goal, a few successes, but also the steadfast forces that undermine doctors’ ability to understand and act on evidence. Moreover, the last decade has seen two new forces that distract from solving the problem. The first is the promise of digital technology, from diagnostic AI systems to big data analytics, which consumes much of the attention. Digital technology is of little help if doctors do not understand it. Second, our efforts to make patients competent and to encourage them to articulate their values are now in conflict with the new paternalistic view that patients just need to be nudged into better behaviour.

This talk will be followed by a drinks reception, all welcome

Joint event with: The Oxford–Berlin Research Partnership

What happens when new artificial intelligence (AI) tools are integrated into organisations around the world?

For example, digital medicine promises to combine emerging and novel sources of data and new analysis techniques like AI and machine learning to improve diagnosis, care delivery and condition management. But healthcare workers find themselves at the frontlines of figuring out new ways to care for patients through, with – and sometimes despite – their data. Paradoxically, new data-intensive tasks required to make AI work are often seen as of secondary importance. Gina calls these tasks data work, and her team studied how data work is changing in Danish & US hospitals (Moller, Bossen, Pine, Nielsen and Neff, forthcoming ACM Interactions).

Based on critical data studies and organisational ethnography, this talk will argue that while advances in AI have sparked scholarly and public attention to the challenges of the ethical design of technologies, less attention has been focused on the requirements for their ethical use. Unfortunately, this means that the hidden talents and secret logics that fuel successful AI projects are undervalued and successful AI projects continue to be seen as technological, not social, accomplishments.

In this talk we will examine publicly known “failures” of AI systems to show how this gap between design and use creates dangerous oversights and to develop a framework to predict where and how these oversights emerge. The resulting framework can help scholars and practitioners to query AI tools to show who and whose goals are being achieved or promised through, what structured performance using what division of labour, under whose control and at whose expense. In this way, data work becomes an analytical lens on the power of social institutions for shaping technologies-in-practice.

In this talk Professor Gina Neff, Oxford Internet Institute and Professor Ian Goldin, Oxford Martin School, will examine publicly known “failures” of AI systems to show how this gap between design and use creates dangerous oversights and to develop a framework to predict where and how these oversights emerge. The resulting framework can help scholars and practitioners to query AI tools to show who and whose goals are being achieved or promised through, what structured performance using what division of labour, under whose control and at whose expense. In this way, data work becomes an analytical lens on the power of social institutions for shaping technologies-in-practice.

In 2020, Governments around the world made the decision to lock down their country to help stop the spread of Covid-19. This led to teaching, meetings, conferences, contacting family and more being conducted from home via the internet.

How did this affect data being used across the world? Did the systems already in place stand-up to the pressure? Was our privacy compromised. As companies and families grapple with how much data they need, we find ourselves in the midst of these important moral deliberations. The pandemic is revealing just how complex the data inter-dependencies are when we need to respond effectively.

Join Sir Tim Berners-Lee, inventor of the World Wide Web, and Professor Sir Nigel Shadbolt, leading researcher in Artificial Intelligence (AI), as they discuss what we have learnt and in what new directions we need to head in the world of data architecture.

On the 30th November it was announced that the Artificial Intelligence computer programme AlphaFold had made a decisive breakthrough in the determination of the 3-D structures of proteins.

The announcement was immediately hailed as one of the major scientific advances of the decade.

Why is it important to understand the 3-D structures of protein, why are they difficult to construct, and what is the nature of AlphaFold’s advance? Why is this so exciting and what further advances in medicine and the other biosciences may result? To find out, join a conversation between Yvonne Jones, Director, Cancer Research UK Receptor Structure Research Group and Charles Godfray, Director, Oxford Martin School, who will explore these fascinating issues.