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Emerging Perspectives in Human-Centered Machine Learning

Ramos, Gonzalo; Suh, Jina; Ghorashi, Soroush; Fiebrink, Rebecca; Bansal, Gagan; Meek, Christoper; Banks, Richard; Amershi, Saleema and Smith-Renner, Alison. 2018. 'Emerging Perspectives in Human-Centered Machine Learning'. In: CHI’19 Extended Abstracts on Human Factors in Computing Systems. Glasgow, United Kingdom. [Conference or Workshop Item] (Forthcoming)

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Abstract or Description

Current Machine Learning (ML) models can make predictions that are as good as or better than those made by people. The rapid adoption of this technology puts it at the forefront of systems that impact the lives of many, yet the consequences of this adoption are not fully understood. Therefore, work at the intersection of people's needs and ML systems is more relevant than ever. This area of work, dubbed Human-Centered Machine Learning (HCML), re-thinks ML research and systems in terms of human goals. HCML gathers an interdisciplinary group of HCI and ML practitioners, each bringing their unique, yet related perspectives. This one-day workshop is a successor of Gillies et al. (2016) and focuses on recent advancements and emerging areas in HCML. We aim to discuss different perspectives on these areas and articulate a coordinated research agenda for the XXI century.

Item Type:

Conference or Workshop Item (Other)

Additional Information:

This paper, published as a CHI Extended Abstract, describes the CHI 2019 workshop on Emerging Perspectives in Human-Centered Machine Learning, to be held in May 2019. Paper authors are the workshop organisers.

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Departments, Centres and Research Units:

Computing
Computing > Embodied AudioVisual Interaction Group (EAVI)

Dates:

DateEvent
20 November 2018Accepted

Event Location:

Glasgow, United Kingdom

Item ID:

25414

Date Deposited:

08 Jan 2019 16:24

Last Modified:

08 Jan 2019 16:25

URI:

http://research.gold.ac.uk/id/eprint/25414

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