Ten years after ImageNet: a 360° perspective on artificial intelligence.

It is 10 years since neural networks made their spectacular comeback. Prompted by this anniversary, we take a holistic perspective on artificial intelligence (AI). Supervised learning for cognitive tasks is effectively solved-provided we have enough high-quality labelled data. However, deep neural network models are not easily interpretable, and thus the debate between blackbox and whitebox modelling has come to the fore. The rise of attention networks, self-supervised learning, generative modelling and graph neural networks has widened the application space of AI. Deep learning has also propelled the return of reinforcement learning as a core building block of autonomous decision-making systems. The possible harms made possible by new AI technologies have raised socio-technical issues such as transparency, fairness and accountability. The dominance of AI by Big Tech who control talent, computing resources, and most importantly, data may lead to an extreme AI divide. Despite the recent dramatic and unexpected success in AI-driven conversational agents, progress in much-heralded flagship projects like self-driving vehicles remains elusive. Care must be taken to moderate the rhetoric surrounding the field and align engineering progress with scientific principles.

Interview with the Hon. Dr Michael Wooldridge: tobacco control was the best buy in health then and it's still the best buy now.

The late 1990s marked a turning point for tobacco control in Australia. In March 1996, the Liberal-National Coalition won government after 13 years of Labor rule. Prime Minister John Howard had campaigned on cutting expenditure, and had long been a proponent of small government and the private sector. Yet within 2 years of taking office, the Howard Government funded Australia's first big budget National Tobacco Campaign and commenced a review of the Tobacco Advertising Prohibition Act 1992 to phase out industry sponsorship of international sporting events. The Honourable Dr Michael Wooldridge, Minister for Health from 1996 to his retirement from politics in 2001, reflects on how these reforms to tobacco control were achieved and how the public health community can best engage with policy makers to advocate for reform. He stresses the importance of public health not being defined by ideology, and that politicians must be scientifically well informed and supported in doing what is in the nation's best interest for public health. He assesses the current state of play and argues more investment in tobacco control is needed today, suggesting it remains the "best buy" in health.

Off-line synthesis of evolutionarily stable normative systems.

Within the area of multi-agent systems, normative systems are a widely used framework for the coordination of interdependent activities. A crucial problem associated with normative systems is that of synthesising norms that will effectively accomplish a coordination task and that the agents will comply with. Many works in the literature focus on the on-line synthesis of a single, evolutionarily stable norm (convention) whose compliance forms a rational choice for the agents and that effectively coordinates them in one particular coordination situation that needs to be identified and modelled as a game in advance. In this work, we introduce a framework for the automatic off-line synthesis of evolutionarily stable normative systems that coordinate the agents in multiple interdependent coordination situations that cannot be easily identified in advance nor resolved separately. Our framework roots in evolutionary game theory. It considers multi-agent systems in which the potential conflict situations can be automatically enumerated by employing MAS simulations along with basic domain information. Our framework simulates an evolutionary process whereby successful norms prosper and spread within the agent population, while unsuccessful norms are discarded. The outputs of such a natural selection process are sets of codependent norms that, together, effectively coordinate the agents in multiple interdependent situations and are evolutionarily stable. We empirically show the effectiveness of our approach through empirical evaluation in a simulated traffic domain.

Full text and figure display improves bioscience literature search.

When reading bioscience journal articles, many researchers focus attention on the figures and their captions. This observation led to the development of the BioText literature search engine, a freely available Web-based application that allows biologists to search over the contents of Open Access Journals, and see figures from the articles displayed directly in the search results. This article presents a qualitative assessment of this system in the form of a usability study with 20 biologist participants using and commenting on the system. 19 out of 20 participants expressed a desire to use a bioscience literature search engine that displays articles' figures alongside the full text search results. 15 out of 20 participants said they would use a caption search and figure display interface either frequently or sometimes, while 4 said rarely and 1 said undecided. 10 out of 20 participants said they would use a tool for searching the text of tables and their captions either frequently or sometimes, while 7 said they would use it rarely if at all, 2 said they would never use it, and 1 was undecided. This study found evidence, supporting results of an earlier study, that bioscience literature search systems such as PubMed should show figures from articles alongside search results. It also found evidence that full text and captions should be searched along with the article title, metadata, and abstract. Finally, for a subset of users and information needs, allowing for explicit search within captions for figures and tables is a useful function, but it is not entirely clear how to cleanly integrate this within a more general literature search interface. Such a facility supports Open Access publishing efforts, as it requires access to full text of documents and the lifting of restrictions in order to show figures in the search interface.

Evidence for showing gene/protein name suggestions in bioscience literature search interfaces.

This paper reports on the results of two questionnaires asking biologists about the incorporation of text-extracted entity information, specifically gene and protein names, into bioscience literature search user interfaces. Among the findings are that study participants want to see gene/protein metadata in combination with organism information; that a significant proportion would like to see gene names grouped by type (synonym, homolog, etc.), and that most participants want to see information that the system is confident about immediately, and see less certain information after taking additional action. These results inform future interface designs.

BioText Search Engine: beyond abstract search.

UNLABELLED: The BioText Search Engine is a freely available Web-based application that provides biologists with new ways to access the scientific literature. One novel feature is the ability to search and browse article figures and their captions. A grid view juxtaposes many different figures associated with the same keywords, providing new insight into the literature. An abstract/title search and list view shows at a glance many of the figures associated with each article. The interface is carefully designed according to usability principles and techniques. The search engine is a work in progress, and more functionality will be added over time. AVAILABILITY: http://biosearch.berkeley.edu.