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An Overview of Artificial Intelligence Ethics and Regulations


In the past 18 months, we have seen a huge rise in the interest of AI development and activation. Countries are developing national strategies, and companies are positioning themselves for the fourth industrial revolution. With this pervasive push of AI, comes also an increased awareness that AIs should act in the interest of a human - and this is not as trivial as one might think. This article provides an overview of several key initiatives that propose ways on approaching AI ethics, regulation and sustainability. As this is a fast evolving field, I aim to update this article regularly.

Artificial Intelligence and Machine Learning: Policy Paper


AI traditionally refers to an artificial creation of human-like intelligence that can learn, reason, plan, perceive, or process natural language[1] . Several issues must be considered when addressing AI, including, socio-economic impacts; issues of transparency, bias, and accountability; new uses for data, considerations of security and safety, ethical issues; and, how AI facilitates the creation of new ecosystems. At the same time, in this complex field, there are specific challenges facing AI, which include: a lack of transparency and interpretability in decision-making; issues of data quality and potential bias; safety and security implications; considerations regarding accountability; and, its potentially disruptive impacts on social and economic structures. Artificial intelligence (AI) traditionally refers to an artificial creation of human-like intelligence that can learn, reason, plan, perceive, or process natural language.

The AI Index 2021 Annual Report Artificial Intelligence

Welcome to the fourth edition of the AI Index Report. This year we significantly expanded the amount of data available in the report, worked with a broader set of external organizations to calibrate our data, and deepened our connections with the Stanford Institute for Human-Centered Artificial Intelligence (HAI). The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence. Its mission is to provide unbiased, rigorously vetted, and globally sourced data for policymakers, researchers, executives, journalists, and the general public to develop intuitions about the complex field of AI. The report aims to be the most credible and authoritative source for data and insights about AI in the world.

The 7 Most Promising Government Led AI Solutions


As the 21st century rages on, success and failure of nations depends not only on their citizenry and governmental leadership, but heavily on the technological visions that countries embrace. If a nation takes the approach of sitting back or standing still as automation and Artificial Intelligence advance at ever increasing rates, that nation is destined to be left behind. However, if a country embraces AI and dedicates significant resources and top minds to ethical implementation, that country is destined to be a leader for decades to come. Recently Steve Mills, Chief AI Ethics Officer & Leader for Artificial Intelligence in the Public Sector, and Partner at Boston Consulting Group said quite eloquently "AI has become table stages for global national economic and technological competitiveness. This goes beyond nations capturing a piece of the large and rapidly growing AI market. AI is poised to transform nearly every industry. There is an imperative for nations to position themselves to integrate AI into these sectors. Particularly those sectors that are economically important to them. Failing to do so could erode their competitive position, creating opportunities for other, more technologically advanced nations to fill the void. This is not just a matter of missed upside potential from the new AI market. It's also about downside risk for every other sector that is economically important to a nation."

The Key Concepts of Ethics of Artificial Intelligence - A Keyword based Systematic Mapping Study Artificial Intelligence

The growing influence and decision-making capacities of Autonomous systems and Artificial Intelligence in our lives force us to consider the values embedded in these systems. But how ethics should be implemented into these systems? In this study, the solution is seen on philosophical conceptualization as a framework to form practical implementation model for ethics of AI. To take the first steps on conceptualization main concepts used on the field needs to be identified. A keyword based Systematic Mapping Study (SMS) on the keywords used in AI and ethics was conducted to help in identifying, defying and comparing main concepts used in current AI ethics discourse. Out of 1062 papers retrieved SMS discovered 37 re-occurring keywords in 83 academic papers. We suggest that the focus on finding keywords is the first step in guiding and providing direction for future research in the AI ethics field.