Artificial Intelligence - Literature Review
With origins dating back to the 1950s Artificial Intelligence (AI) is not necessarily new. However, interest in AI has been rekindled over the last few years, in no small measure due to the rapid advancement of the technology and its applications to real- world scenarios. In order to create policy in the field, understanding the literature regarding existing legal and regulatory parameters is necessary. This Literature Review is the first in a series of reports that seeks to map the development of AI, both generally and in specific sectors, culminating in a stakeholder analysis and contributions to policy-making. This Review analyses literature on the historical development of the technology, its compositional makeup, sector- specific impacts and solutions and finally, overarching regulatory solutions.
Edited by Amber Sinha and Udbhav Tiwari; Research Assistance by Sidharth Ray
With origins dating back to the 1950s Artificial Intelligence (AI) is not necessarily new. With an increasing number of real-world implications over the last few years, however, interest in AI has been reignited over the last few years.
The rapid and dynamic pace of development of AI have made it difficult to predict its future path and is enabling it to alter our world in ways we have yet to comprehend. This has resulted in law and policy having stayed one step behind the development of the technology.
Understanding and analyzing existing literature on AI is a necessary precursor to subsequently recommending policy on the matter. By examining academic articles, policy papers, news articles, and position papers from across the globe, this literature review aims to provide an overview of AI from multiple perspectives.
The structure taken by the literature review is as follows:
- Overview of historical development
- Definitional and compositional analysis
- Ethical & Social, Legal, Economic and Political impact and sector-specific solutions
- The regulatory way forward
This literature review is a first step in understanding the existing paradigms and debates around AI before narrowing the focus to more specific applications and subsequently, policy-recommendations.
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