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Showing 1–7 of 7 results
Advanced filters: Author: Mona Sloane Clear advanced filters

  • There is no shortage of opinions on the impact of artificial intelligence and deep learning. We invited authors of Comment and Perspective articles that we published in roughly the first half of 2019 to look back at the year and give their thoughts on how the issue they wrote about developed.

    • Alexander S. Rich
    • Cynthia Rudin
    • Jack Stilgoe
    Special Features
    Nature Machine Intelligence
    Volume: 2, P: 2-9

  • Developers of artificial intelligence must learn to collaborate with social scientists and the people affected by its applications.

    • Mona Sloane
    Comments & Opinion
    Nature
    Volume: 605, P: 9

  • Sloane and colleagues review emerging new dimensions of risks associated with materiality and AI algorithms run on pervasive sensors.

    • Mona Sloane
    • Emanuel Moss
    • Vijay Janapa Reddi
    Reviews
    Nature Machine Intelligence
    Volume: 7, P: 334-345

  • To create less harmful technologies and ignite positive social change, AI engineers need to enlist ideas and expertise from a broad range of social science disciplines, including those embracing qualitative methods, say Mona Sloane and Emanuel Moss.

    • Mona Sloane
    • Emanuel Moss
    Comments & Opinion
    Nature Machine Intelligence
    Volume: 1, P: 330-331

  • An increasing number of regulations demand transparency in automated decision-making processes such as in automated online recruitment. To provide meaningful transparency, Sloane et al. propose the use of ‘nutritional’ labels that display specific information about an automated decision system, depending on the context.

    • Mona Sloane
    • Ian René Solano-Kamaiko
    • Julia Stoyanovich
    Reviews
    Nature Machine Intelligence
    Volume: 5, P: 187-195

  • Cysteine cathepsins are proteolytic enzymes whose expression is increased in both tumour and tumour-associated cells. What is known about the extracellular and intracellular functions of these enzymes in cancer?

    • Mona Mostafa Mohamed
    • Bonnie F. Sloane
    Reviews
    Nature Reviews Cancer
    Volume: 6, P: 764-775

  • Whole-genome sequencing, transcriptome-wide association and fine-mapping analyses in over 7,000 individuals with critical COVID-19 are used to identify 16 independent variants that are associated with severe illness in COVID-19.

    • Athanasios Kousathanas
    • Erola Pairo-Castineira
    • J. Kenneth Baillie
    ResearchOpen Access
    Nature
    Volume: 607, P: 97-103