ChomGPT

I got pointed out at an interesting NTY editorial of March 8, 2023, on ChatGPT written by Noam Chomsky, Ian Roberts and Jeffrey Watumull.

“we fear that the most popular and fashionable strain of A.I. — machine learning — will degrade [linguistics] and debase our ethics by incorporating into our technology a fundamentally flawed conception of language and knowledge.”

Starting with a quote of Jorge Luis Borges, most appropriately for the dystopian prospects brought by the new chatbots. And seeing the arrival of these machines as something trivial that operates in contrast with the human mind by making use of terabytesque amounts of data and (cleverly) extrapolating to suit the question. Which is to state that they are merely (?) much better interfaces at reproducing patterns found in their data bases. This remains a technical feat but given the lack of reliability of their output (cf my exam answers) and the correlated lack of uncertainty in their assessment, they are very much useless at explanations. (But sometimes usefull as typewriting monkeys for recommendation letters.)

“The crux of machine learning is description and prediction; it does not posit any causal mechanisms or physical laws.”

The second part of the tribune points out the amorality of such platforms, unable to reach a moral position. This is illustrated by Q&As about the morality of terraforming an other planet (which I cannot connect with morality if there is no sentient life on that planet). While I see the point as a fundamental distinction between humans and AIs, I would feel uncomfortable with the latter producing moral judgements as this would imply a choice of moral rules in their training, as there is no universal moral ground beyond the “obvious”… (Actually, by presenting arguments in an authoritative manner, rarely with provisions for being wrong or incomplete, ChatGPT is agreeing on lying by omission!)

“Given the amorality, faux science and linguistic incompetence of these systems, we can only laugh or cry at their popularity.”

MCMC postdoc positions at Bocconi

[A call for postdoc candidates to work in Milano with Giacomo Zanella in the coming years under ERC funding. In case you are interested with a postdoctoral position with me at Paris Dauphine on multi-agent decision-making, data sharing, and fusion algorithms, do not hesitate to contact me, the official call for applications should come up soon!]

Three postdoc positions available at Bocconi University (Milan, Italy), under the supervision of Giacomo Zanella and funded by the ERC Starting Grant “Provable Scalability for high-dimensional Bayesian Learning”. Details and links to apply available online.

The deadline for application is 28/02/2023 and the planned starting date is 01/05/2023 (with some flexibility). Initial contracts are for 1 year and are extendable for further years under mutual agreement.

Candidates will conduct research on computational aspects of statistical and machine learning methods, with a particular focus on Bayesian methodologies. The research activity, both in terms of specific topic and research approach, can adapt to the profile and interests of the successful candidates. Beyond working with the supervisor and coauthors on topics related to the grant project (see here and there for more details on the research topics of the supervisor and grant project), candidates will get the chance to interact with various faculty members, postdocs and PhD students of the Stats&ML group at Bocconi (see e.g. researchers at Bocconi).

Interested candidates can write to giacomo zanella at unibocconi for more information about the positions.

four positions in statistics at Warwick [reposted]

Assistant and Associate Professor positions in Statistics and Machine Learning at Warwick

Outstanding and enthusiastic academics are sought by the Department of Statistics at Warwick, one of the world’s most prominent and most research active departments of Statistics. The Department has close relations with the co-located Mathematics Institute and Department of Computer Science and with other departments such as Economics and the Warwick Business School. Four permanent posts are available, which reflects the strong commitment of the University of Warwick to invest in Statistics and Machine Learning:

Assistant Professor, Applied Statistics

Associate Professor, Machine Learning

Assistant Professor, Machine Learning

Associate Professor, Statistics

Applicants should have evidence or promise of world-class research excellence and ability to deliver high quality teaching across our broad range of degree programmes. At Associate Professor level, applicants should have an outstanding publication record. Other positive indicators include enthusiasm for engagement with other disciplines, within and outside the Department and, at Associate Professor level, a proven ability to secure research funding. Further details of the requirements for each of the four positions can be found at https://warwick.ac.uk/statjobs.

The Department of Statistics is committed to promoting equality and diversity, holding an Athena SWAN Silver award which demonstrates this commitment. We welcome applicants from all sections of the community and will give due consideration to applicants seeking flexible working patterns, and to those who have taken a career break. Further information about working at the University of Warwick, including information about childcare provision, career development and relocation is at https://warwick.ac.uk/services/humanresources/workinghere/.

Informal inquiries can be addressed to Professors Jon Forster (J.J.Forster@warwick.ac.uk) or Adam Johansen (A.M.Johansen@warwick.ac.uk) or to any other senior member of the Warwick Statistics Department.

Closing date: December 12, 2022.

More details and a link to the application forms: https://warwick.ac.uk/statjobs

Further information about the Department of Statistics: https://warwick.ac.uk/stats

Further information about the University of Warwick: https://www2.warwick.ac.uk/services/humanresources/jobsintro/furtherparticulars

 

Data science for social good fellowships [DSSGx UK 2023]

Warwick is (again) running a 12-week summer programme bringing together some of the top student talents from data science, machine learning and artificial intelligence, all over the World, to work on real-world data science challenges and deliver positive social impact. Applications for DSSG 2023 are now OPEN! Click here for the application form (please read the information carefully) and click here for the FAQs for 2023. (The application also works for a similar programme in Kaiserslauten, Germany.

DSSG helps not-for-profit organisations and government bodies to achieve more with their data by enhancing their services, interventions and outreach, helping fulfil their mission of improving the world and people’s lives.

The programme gives not-for-profit organisations and government bodies unprecedented access to inspiring, top-tier data science talent. This helps build their capacity to use cutting-edge quantitative methods to address societal challenges in areas such as education, health, energy, public safety, transportation and economic development.

At the same time, it provides intensive case-based and supported training to students to create industry-standard data science products in collaboration with government agencies and NGOs, to deliver positive social impact. And it builds a world-wide community of data scientists who care about the social good.

In 2019, the University of Warwick together with the Alan Turing Institute brought DSSG to the UK. The University of Warwick has run it each year since and now preparation is well underway for DSSGx UK 2023, which will be held at the University of Warwick, UK, from 5 June to 25 August.

Ocean’s four!

Fantastic news! The ERC-Synergy¹ proposal we submitted last year with Michael Jordan, Éric Moulines, and Gareth Roberts has been selected by the ERC (which explains for the trips to Brussels last month). Its acronym is OCEAN [hence the whale pictured by a murmuration of starlings!], which stands for On intelligenCE And Networks​: Mathematical and Algorithmic Foundations for Multi-Agent Decision-Making​. Here is the abstract, which will presumably turn public today along with the official announcement from the ERC:

Until recently, most of the major advances in machine learning and decision making have focused on a centralized paradigm in which data are aggregated at a central location to train models and/or decide on actions. This paradigm faces serious flaws in many real-world cases. In particular, centralized learning risks exposing user privacy, makes inefficient use of communication resources, creates data processing bottlenecks, and may lead to concentration of economic and political power. It thus appears most timely to develop the theory and practice of a new form of machine learning that targets heterogeneous, massively decentralized networks, involving self-interested agents who expect to receive value (or rewards, incentive) for their participation in data exchanges.

OCEAN will develop statistical and algorithmic foundations for systems involving multiple incentive-driven learning and decision-making agents, including uncertainty quantification at the agent’s level. OCEAN will study the interaction of learning with market constraints (scarcity, fairness), connecting adaptive microeconomics and market-aware machine learning.

OCEAN builds on a decade of joint advances in stochastic optimization, probabilistic machine learning, statistical inference, Bayesian assessment of uncertainty, computation, game theory, and information science, with PIs having complementary and internationally recognized skills in these domains. OCEAN will shed a new light on the value and handling data in a competitive, potentially antagonistic, multi-agent environment, and develop new theories and methods to address these pressing challenges. OCEAN requires a fundamental departure from standard approaches and leads to major scientific interdisciplinary endeavors that will transform statistical learning in the long term while opening up exciting and novel areas of research.

Since the ERC support in this grant mostly goes to PhD and postdoctoral positions, watch out for calls in the coming months or contact us at any time.