AI

22/07/2020 – AI3SD Online Seminar Series: Design Fiction as a method and why we might use it to consider AI – Dr Naomi Jacobs

  • Post author:
  • Post category:

AI is a fast moving field that is rapidly advancing and becoming embedded in a multitude of sectors and applications. With such a fast pace, and excitement over the possibilities it allows, there is often a rush to get things going. This being the case, sometimes not enough time is spent considering the implications and unforeseen outcomes that might come from the introduction of new technologies, processes and practices. Ideas that seem plausible and useful can turn out to be problematic when actually implemented, by which time it is often too late. By using the methodology of speculative design, we can more closely examine these implications and outcomes before the technologies become a reality. This talk will introduce speculative design and give some examples of design fiction, a method wherein objects from fictional futures or alternate presents are created to provoke discussion and explore possibilities.

Continue Reading22/07/2020 – AI3SD Online Seminar Series: Design Fiction as a method and why we might use it to consider AI – Dr Naomi Jacobs

07/07/2020 – AI4Good @ WebSci20

  • Post author:
  • Post category:

This year the AI3SD Network+ (Artificial Intelligence and Augmented Intelligence for Automated Investigations for Scientific Discovery) will be running a workshop at the WebSci20 Conference in Southampton, UK. Artificial and Augmented Intelligence systems have the potential to make a real difference in the scientific discovery domain however this brings a new wealth of ethical and societal implications to consider with regards to this research (e.g. human enhancement, algorithmic biases, risk of detriment). This workshop looks to explore the ethical and societal issues centered around using intelligent technologies (Artificial Intelligence, Augmented Intelligence, Machine Learning, and in general Semantic Web Knowledge Technologies) to further scientific discovery, with a strong consideration of data ethics and algorithmic accountability. Advances in technology and software are rarely inherently bad in themselves, however that unfortunately does not preclude them from being subverted to ill intent by others; furthermore, as demonstrated by the examples above, even an unintentional lack of care towards ethical codes and algorithmic accountability can lead to societal and ethical implications of scientific discovery. It is our responsibility as researchers to consider these issues in our research; are we conducting studies ethically? What ethical codes can we put in place for scientific discovery research to mitigate against ethical and societal issues. These are really important issues, and they require an interdisciplinary focus between scientists, social scientists and technical experts in order to be comprehensively addressed.

Continue Reading07/07/2020 – AI4Good @ WebSci20
Read more about the article 01/07/2020 – AI3SD Online Seminar Series: Drug Repositioning for COVID-19 – Professor John Overington

01/07/2020 – AI3SD Online Seminar Series: Drug Repositioning for COVID-19 – Professor John Overington

https://www.youtube.com/watch?v=gcgeTVfiVl4&ab_channel=AI4ScientificDiscovery Interview: Dr Wendy Warr interviewed John prior to this seminar. This interview can be found here: https://eprints.soton.ac.uk/441804/ Abstract: Pandemics, such as Covid-19. are by definition essentially unanticipatable and rapid onset. Features…

Continue Reading01/07/2020 – AI3SD Online Seminar Series: Drug Repositioning for COVID-19 – Professor John Overington

01/07/2020 – AI3SD Online Seminar Series: Drug Repositioning for COVID-19 – Professor John Overington

  • Post author:
  • Post category:

Pandemics, such as Covid-19. are by definition essentially unanticipatable and rapid onset. Features unfortunately incompatible with current industry capabilities in drug discovery. This has led to a large number of studies, both theoretical and experimental to reposition, or reuse an existing drug for Covid-19 therapy. There are some general patterns of success in historical repositioning that point to the most likely strategies for drug repositioning, and also, following some specific data gathering and curation, to point towards specific actionable activities for Covid-19. The presentation will briefly overview drug repositioning as a general strategy, and then the focussed application of core concepts towards the treatment of Covid-19.

Continue Reading01/07/2020 – AI3SD Online Seminar Series: Drug Repositioning for COVID-19 – Professor John Overington
Read more about the article 9-11/03/2020 – AI3SD, Dial-a-Molecule & Directed Assembly: AI for Reaction Outcome and Synthetic Route Prediction – DeVere Tortworth Court Hotel, Gloucestershire

9-11/03/2020 – AI3SD, Dial-a-Molecule & Directed Assembly: AI for Reaction Outcome and Synthetic Route Prediction – DeVere Tortworth Court Hotel, Gloucestershire

  • Post author:
  • Post category:

This is a joint meeting between the Dial-a-Molecule, Directed Assembly and AI3SD (Artificial Intelligence and Augmented Intelligence for Automated Investigations for Scientific Discovery) Networks. The meeting will examine the state of the art and future opportunities in the use of Artificial Intelligence to predict the outcome of unknown chemical reactions, and consequently design optimum synthetic routes to desired molecules. A wide variety of AI approaches will be illustrated including expert systems, statistical methods, mechanism based and Machine Learning. The meeting will also consider: Data sourcing, sharing, and quality. Automated experimentation to generate reaction knowledge. Theoretical calculations to enrich or replace experimental data. The meeting will include talks to introduce the breadth of the area to all participants. Discussion sessions and opportunities to develop collaborations will be a key aspect of the meeting.

Continue Reading9-11/03/2020 – AI3SD, Dial-a-Molecule & Directed Assembly: AI for Reaction Outcome and Synthetic Route Prediction – DeVere Tortworth Court Hotel, Gloucestershire
Read more about the article 31/01/2020 – AI3SD, OSM & RSC-CICAG: AI and ML in Drug Discovery: Predicting Bioactive Molecules when there is No Target

31/01/2020 – AI3SD, OSM & RSC-CICAG: AI and ML in Drug Discovery: Predicting Bioactive Molecules when there is No Target

Back in January 2019 AI3SD announced their first funding call. We funded 3 pilot projects, and one of the successful applicants of this funding call was Professor Mat Todd from…

Continue Reading31/01/2020 – AI3SD, OSM & RSC-CICAG: AI and ML in Drug Discovery: Predicting Bioactive Molecules when there is No Target

31/01/2020 – AI3SD, OSM & RSC-CICAG: AI and ML in Drug Discovery: Predicting Bioactive Molecules when there is No Target

  • Post author:
  • Post category:

This one-day meeting concerns the application of machine learning/artificial intelligence (ML/AI) approaches to the discovery of new drug leads. Specifically the meeting is about cases where the biological target is not clearly established - so-called phenotypic drug discovery. The meeting centers on a real example - a competition run by Open Source Malaria (OSM), funded by a grant from the EPSRC/AI3SD+ Network. Data on active and inactive compounds in one OSM antimalarial series were published online, and anyone was able to submit a model able to predict the actives. The models were judged against a dataset that was kept private, and the winners were asked to use their models to predict novel molecules. These are currently being made in the lab and biologically evaluated, and the results will be reported at the meeting, providing a real-world test, and a complete case study, of the capabilities of ML/AI approaches to accelerate modern drug discovery. We will hear from some of the eleven competition entrants about how their models were constructed, and will have other presentations on related developments. We hope during this meeting to establish which approaches worked well, which did not, and why. All those interested in the application of ML/AI methods to drug discovery are encouraged to attend. The meeting is free, but there will be a cap on numbers, meaning first come first served, meaning registration is essential. Lunch will be provided as part of this event. GitHub Repository: https://github.com/OpenSourceMalaria/Series4_PredictiveModel

Continue Reading31/01/2020 – AI3SD, OSM & RSC-CICAG: AI and ML in Drug Discovery: Predicting Bioactive Molecules when there is No Target