In the wake of the pandemic, the outlines of a new kind of digital workplace are starting to emerge. Get a glimpse of the future in this short video. Large numbers of employees have adjusted successfully to working remotely. Many businesses are looking for new ways to support online productivity and strengthen business resiliency with remote capabilities, while ensuring a safe return to work for on-site employees. So what does the future of work look like?
As AI-powered systems increasingly mediate consequential decision-making, their explainability is critical for end-users to take informed and accountable actions. Explanations in human-human interactions are socially-situated. AI systems are often socio-organizationally embedded. However, Explainable AI (XAI) approaches have been predominantly algorithm-centered. We take a developmental step towards socially-situated XAI by introducing and exploring Social Transparency (ST), a sociotechnically informed perspective that incorporates the socio-organizational context into explaining AI-mediated decision-making. To explore ST conceptually, we conducted interviews with 29 AI users and practitioners grounded in a speculative design scenario. We suggested constitutive design elements of ST and developed a conceptual framework to unpack ST's effect and implications at the technical, decision-making, and organizational level. The framework showcases how ST can potentially calibrate trust in AI, improve decision-making, facilitate organizational collective actions, and cultivate holistic explainability. Our work contributes to the discourse of Human-Centered XAI by expanding the design space of XAI.
COVID-19 has turned the world of work on its head, with many of us having spent most of 2020 separated from our colleagues and logging-in to greet each other every day from our bedrooms, living spaces, and other cobbled-together places of work. It's a year that has asked a lot of us all, and with 2021 now – somehow – on the horizon, many will be wondering what the next 12 months has in store. One thing seems certain: the new remote-working landscape hastily hammered out by 2020 won't be disappearing any time soon. In fact, working from home at least part of the time looks set to be the new way of doing things for the foreseeable future. And while organizations might have a better grasp on the technical challenges than they did at the start of the year, there is still a litany of issues to overcome if we want to make this "new normal" truly work.
Other than viewing every cough with suspicion and fear, battling COVID-19 has made working from home, a norm today. As humans, we are conditioned to search for silver linings in a storm, so the question arises- What's the silver lining here? Well, other than the synchronized show of solidarity across borders and balconies, the fast-tracking of digital transformations in companies- big and small, definitely tops the list. However, for your companies this definitely holds true. As more states move towards a lockdown, if your business doesn't hop onto the digital bandwagon, then your wheels will turn rusty with inactivity.
Decades of research in artificial intelligence (AI) have produced formidable technologies that are providing immense benefit to industry, government, and society. AI systems can now translate across multiple languages, identify objects in images and video, streamline manufacturing processes, and control cars. The deployment of AI systems has not only created a trillion-dollar industry that is projected to quadruple in three years, but has also exposed the need to make AI systems fair, explainable, trustworthy, and secure. Future AI systems will rightfully be expected to reason effectively about the world in which they (and people) operate, handling complex tasks and responsibilities effectively and ethically, engaging in meaningful communication, and improving their awareness through experience. Achieving the full potential of AI technologies poses research challenges that require a radical transformation of the AI research enterprise, facilitated by significant and sustained investment. These are the major recommendations of a recent community effort coordinated by the Computing Community Consortium and the Association for the Advancement of Artificial Intelligence to formulate a Roadmap for AI research and development over the next two decades.