Explainability in Process Mining: A Framework for Improved Decision-Making

TL;DR: In this paper, the authors argue that in translating ethical principles for digital technologies into ethical practices, even the best efforts may be undermined by some unethical risks, such as ethics shopping, ethics bluewashing, ethics lobbying, ethics dumping, and ethics shirking.

TL;DR: In this paper , a meta-survey of challenges and future research directions in explainable AI is presented, which is organized in two themes: (1) general challenges and research directions of XAI and (2) challenge and research direction of XA based on machine learning life cycle's phases: design, development and deployment.

Abstract: This chapter explores the relationship between disability and improvisation within dance, drawing from a number of dancers’ own views about the place of improvisation in their making and performance practice, and referencing work that deliberately incorporates improvisation as a device to blur the boundaries between the fixed and the fluid. The chapter focuses on the role of contact improvisation in the work of disabled dancers. By prioritizing the interaction with different bodies, contact improvisation can support an aesthetic based on sensory adjustment and accommodation. Conversely, contact improvisation might be seen to ‘smooth over’ disorder and involuntary motion that disabled dancing bodies offer as a reconceptualization of the acceptable aesthetic in dance. The discussion also includes reference to Notturnino (2014), a work of choreography by Thomas Hauert, which was commissioned for the Candoco Dance Company and offers a way to examine how dance improvisation has adopted disability in its shifting physical aesthetic.

TL;DR: An assessment of these practical frameworks with the lens of known best practices for impact assessment and audit of technology, and identifies gaps in current AI ethics tools in auditing and risk assessment that should be considered going forward.