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30/06/2019 - AI3SD AI 4 Good Workshop @ WebSci9 - Boston, US

posted 28 Jan 2019, 06:59 by Samantha Kanza   [ updated 26 Feb 2019, 08:48 ]

This year the AI3SD Network+ (Artificial Intelligence and Augmented Intelligence for Automated Investigations for Scientific Discovery) will be running a workshop at the WebSci19 Conference in Boston. 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.  

We are living through a data revolution, which will be as transformative of our society as the industrial revolution. Algorithms, and in particular, learning algorithms, are the engines of this revolution. ‘Intelligent’ algorithmic systems impact many areas of our personal and professional lives, making decisions based on prior ‘learned’ knowledge. The use of learning algorithms and has the potential to revolutionise scientific discoveries. However, these discoveries have the potential to be simultaneously beneficial and detrimental at the same time if they are not undertaken in a responsible and ethical manner. A few of these Major themes for this workshop are detailed below, although all other contributions surrounding the use of AI in Scientific Discovery are welcomed! 
  • AI in Drug Discovery & Heathcare – Intelligent technologies can be vastly useful in drug discovery and healthcare research as machine learning algorithms can be applied to vast linked datasets to make predictions that humans could not. However, this research may not apply to certain minority groups depending on the data used in the system. This may not be as a consequence of intentional algorithmic/data bias but equally is something that should have been addressed by ethical discussions at the start of a project, as “excluding minorities from healthcare research limits the ability to appropriately care for these population and skews the scientific understanding of disease” and indeed drugs to fight and cure these diseases.  
  • AI for Chemicals and Materials Discovery – Molecular compounds and materials underpin just about every aspect of our lives, from sustainable energy to healthcare. Society’s demands for enhanced performance is far outweighing our capability to discover materials that deliver it, so it is unsurprising that researchers are looking at using artificial intelligence and machine learning technologies to explore this space and speed up the discovery of new chemicals. However, do the algorithms to discover these chemicals and materials take into account whether they are environmentally friendly? Or whether certain chemicals could be psychoactive or extremely explosive? Whether materials could be used for ill intent? Does this mean chemicals/materials like this shouldn’t be investigated?
Key Dates:
  • Calls for Papers Opens: 22nd February 2019
  • Paper Submission: 1st April 2019
  • Notification of Acceptance: 16th April 2019 
  • Camera Ready Papers: 1st May 2019 
  • Workshop At WebSci19: 20th June 2019