RethinkAI: Designing the Impact of AI in the Future of Work (original) (raw)
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RethinkAI: Designing the human and AI relationship in the future of work
2019
The innovation landscape is drastically changing due to the adoption of Artificial Intelligence (AI), as whole industries are incorporating AI into smart products and automated processes. Designing AI for industry 4.0 requires revolutionary thinking. It requires the emergence of new design paradigms that build designers' ability to navigate the ethical and socioeconomic issues that AI brings in the future of work. This research develops RethinkAI™ a new participatory design method to address this gap. The paper focuses specifically on how to design the relationship of humans and AIs working together. RethinkAI™ builds an interactive, social way for designers and transdisciplinary teams to explore this relationship. It creates insights on how human and AI strengths can be designed together in a co-evolving relationship in the future of work. RethinkAI™ was designed, tested and refined through a series of three workshops. The method was evaluated in a final workshop with 24 multin...
Beijing law review, 2024
This scholarly paper examines the pioneering approach of the United Kingdom in integrating Artificial Intelligence (AI) within the workplace, particularly through its model of consulting workers. Drawing upon the case studies of Jaguar Land Rover and the Royal Bank of Scotland, the paper explores how this inclusive approach not only enhances productivity and innovation but also ensures ethical alignment and worker satisfaction in the AI-driven workplace. The analysis culminates in recommendations for a global legal framework inspired by the UK model, advocating for inclusivity, transparency, and adaptability in AI deployment. The research methodology adopted for this work primarily involves a qualitative analysis of existing literature and case studies. Sources include academic journals, industry reports, and policy documents, analysed to extract insights into the benefits and challenges of the UK's consultative approach to AI in workplaces. The paper synthesises these findings to propose a framework for global application. The primary limitation of this study is its reliance on secondary sources, which may not fully capture the breadth of on-ground challenges and nuances in AI implementation across different industries and cultural contexts. Additionally, the rapid evolution of AI technology and its applications means that some insights may quickly become outdated.
Journal of Ethics and Emerging Technologies, 2022
Davenport and Miller's book "Working with AI: Real stories of human-machine collaboration" (MIT Press, 2022) is focused on showing and analyzing how AI is currently implemented in various organizations across the globe. This by itself makes it an interesting contribution to current scholarship, since so much of what is written about emerging technologies either focuses on technologies that have not yet been commercially deployed, or mixes present and future, making it at times hard to discern where the line between what exists in the present ends and what may come to exist in the future begins. Davenport and Miller's focus on the present allows for a much more grounded debate about the social implications of AI technologies on humans, since instead of projecting either utopian or dystopian schemes on the future, the book deals with processes that are occurring today, that pose ethical challenges today, and that are having impact on humans today. Another important feature that sets this book apart is the richness of cases that the two authors bring to the table. The book offers no less than twenty-nine case studies, from different economic sectors, with different application types, and from different corners of the world (specifically from North America and Asia). Each case study includes a concise, yet very informative, depiction of an application of an AI technology (or sometimes a combination of a few AI technologies) in a certain organization. The authors skillfully offer sufficient description to make the ways in which the AI is used in each case clear, yet without going into too many details which might render the text tedious. All in all, this richness of case studies culminates in quite an informative text. Thus, if you are interested in how AI is currently deployed in a specific field, you will, most probably, find a relevant case study in this book. Moreover, within the mix of AI applications discussed in the book, you can also find some of the more ethically challenged applications, such as in the fields of healthcare and policing, which may appeal specifically to scholars who focus on risks within AI. Unfortunately, the book's rigor with regards to depicting the current applications of AI by various organizations in a variety of settings, is not matched by a high level of analysis of each case, or of the general trends that emerge from them. Its problematic research method, its apparent lack of interdisciplinary outlook, and its adoption of the business-world narrative regarding AI, severely handicap it, and its ability to get a good read of the social implications and ethical challenges of AI technologies. Therefore, while I found the depictions of each case quite interesting, I found the debates that followed and the conclusions that the authors asked to draw from each case somewhat limited and flawed. With regards to methods, the initial idea of the two authors seems rather solid: to study the application of these AI technologies from the "frontline"; that is from the perspective of
Some implications of AI in workplace
Some implications of using artificial intelligence at the workplace have come with challenges. A recent example of that is the AI-related firing of delivery drivers of Amazon. This study wonders whether this assertion has any bearing and, if so, how it may be established. This study investigates some of the implications of using artificial intelligence at the workplace; a case study of Amazon Company. The study used a qualitative case study method involving reviewing secondary data sources through thematic analysis. The research conducted has shown that AI influences human use of AI in firing drivers in Amazon Company. It suggested direct and indirect outcomes of using AI in the workplace, particularly in the Amazon case study. It brought about some advantages and disadvantages of these implications and discussed the ethical part of AI at the workplace. The study recommends further research in this area.
What's Left for Us? AI, Ethics and the Future of Work
2024
AI is not just technology—it’s rewriting the rules of work and society, raising hard questions we can’t ignore. What’s Left for Us? doesn’t shy away from the complexity of it all. This isn’t about AI as a silver bullet or a new gadget for the workplace. It’s about the transformation unfolding before us, reshaping industries, displacing jobs, and altering the structure of our day-to-day lives. This book pulls no punches. In Part One, you’ll find a straightforward analysis of AI’s capabilities and ethical concerns. It gets into everything from AI’s effect on privacy and inequality to the biases programmed into its algorithms. Part Two digs into the future of work in an AI-driven world, questioning who wins and who loses, and how we can stay responsible in a society increasingly influenced by automation and data. The writing is sharp, direct, and grounded in reality. What’s Left for Us? is for readers who aren’t looking for easy answers but want to understand the world we’re building with AI—its benefits, dangers, and the responsibilities we face.
Positioning AI as a Partner in Work and Action: A Library Research Journal
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This study explores the potential and challenges of AI in professional settings, focusing on its ethical, socioeconomic , and practical implications, and proposes strategies for fostering human-AI collaboration. Design/Methodology/Approach: The systematic literature review methodology analyzes academic papers, books, reports, and articles on AI's applications, challenges, and ethical considerations across various electronic databases. Originality/Value: This study provides a comprehensive overview of AI integration in collaborative work environments, highlighting its benefits and challenges, and emphasizing the need for responsible deployment and proactive policies. Findings: The literature review highlights the challenges of integrating AI into collaborative work environments, including ethical concerns, algorithmic bias, and job displacement, but also highlights potential opportunities for improved human-AI collaboration.
2019
In January 2011, a supercomputer called IBM Watson played a game Jeopardy! and won against two of its best human players in the history of this game, Ken Jennings and Brad Rutter. "And winning at Jeopardy! requires mastering of pattern matching and complex communication, repeatedly, accurately, and almost simultaneously." (Brynjolfsson and McAfee, 2016, p. 24- 27) Ever since the discussion of human superiority versus machines is ongoing and it is one of the hottest topics of nowadays. This research aims to understand the global implications of AI and advanced technologies on jobs across the industry and find practical solutions to support industry productivity growth and novel ideas. In the first part of the study, based on the literature review, the human plus machine collaboration is carefully elaborated and made as a recommendation for the organizations to win the race against competitors and attract and keep their top talent. We are witnessing the unprecedented level o...
European Conference on the Impact of Artificial Intelligence and Robotics
Artificial Intelligence (AI) is a highly disruptive technology that will have major effects on the business world over the coming years. It has the potential to allow companies to achieve major efficiency gains and a more productive workforce through automating existing processes, providing deeper levels of analytics, providing better customer support, and increasing security. On the other hand, it may lead to lower staff levels and a drop in existing employee morale. Given the complexities of these projects, AI will only benefit organisations if they understand its capabilities in addition to its shortcomings. This investigation addresses the predicted impact on skills, roles and employee morale of artificial intelligence on the workforce of the future as AI continues to become more prevalent in our society. We investigate these impacts of AI specifically across four key industries by engaging in interviews with experts in the field to answer two research questions: (i) What are th...
Artificial intelligence and the world of work, a co‐constitutive relationship
Journal of the Association for Information Science and Technology, 2020
The use of intelligent machines—digital technologies that feature data‐driven forms of customization, learning, and autonomous action—is rapidly growing and will continue to impact many industries and domains. This is consequential for communities of researchers, educators, and practitioners concerned with studying, supporting, and educating information professionals. In the face of new developments in artificial intelligence (AI), the research community faces 3 questions: (a) How is AI becoming part of the world of work? (b) How is the world of work becoming part of AI? and (c) How can the information community help address this topic of Work in the Age of Intelligent Machines (WAIM)? This opinion piece considers these 3 questions by drawing on discussion from an engaging 2019 iConference workshop organized by the NSF supported WAIM research coordination network (note: https://waim.network).
AI in society and culture: decision making and values
2020
With the increased expectation of artificial intelligence, academic research face complex questions of human-centred, responsible and trustworthy technology embedded into society and culture. Several academic debates, social consultations and impact studies are available to reveal the key aspects of the changing human-machine ecosystem. To contribute to these studies, hundreds of related academic sources are summarized below regarding AI-driven decisions and valuable AI. In details, sociocultural filters, taxonomy of human-machine decisions and perspectives of value-based AI are in the focus of this literature review. For better understanding, it is proposed to invite stakeholders in the prepared large-scale survey about the next generation AI that investigates issues that go beyond the technology.