Article 1:
How AI will revolutionize the practice of law

In this commentary for the Brookings Institute, John Villasenor argues that law firms that leverage AI technologies will be able to offer services at lower cost, higher efficiency, and with more favorable outcomes in litigation.

He suggests that such technological innovation will spur the creation of new legal tech companies, as well as new opportunities to use AI for more fully automated provision of legal services.

He concludes, however, that while AI will fundamentally reshape the landscape of legal services, by leveling the playing field, it will underscore the importance of the human element in the practice of law.

Source:

The Brookings Institution

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Article 2:
A new AI lexicon:
social good

This guest post by Doaa Abu-Elyounes and Karine Gentelet reviews the challenges of defining AI as ethical, responsible, or good.

These definitions often judge AI technology’s social impact as a whole, even though the applications have very different impacts on different groups of society.

The essay highlights the lack of substance inherent to the many initiatives surrounding “AI for good”; the various contributions to date are characterized as often broad, aspirational, and hollow, they tend to focus on neglected societal needs.and they often differentiate between economic impact and the societal impact and advantages.

They conclude with a call for a more nuanced approach that examines how each AI system impacts disadvantaged and marginalized groups.

Source:

Medium/AI Now Institute

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Article 3:
AI should augment human intelligence, not replace it

In this HBR contribution, David De Cremer and Garry Kasparov develop their vision of how human intelligence can work with artificial intelligence to produce augmented intelligence.

They begin by suggesting that AI and human beings bring different strengths to the table: AI-based machines are fast, more accurate, and consistently rational, where human beings are often intuitive, emotional, and culturally sensitive.

They suggest that augmented intelligence bring together the strengths of each, and that the process of how players and computers interact determines how efficient the result will be.

Their recommendation is to anticipate how artificial intelligence will impact how humans think and act, and work to integrate the new technologies ambitiously and strategically into organizations.

Source:

Harvard Business Review

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Article 4:
Achieving a “Good AI Society”:
Comparing the aims and progress of the EU and the US

This article, authored by the Oxford Internet Institute, provides a comparative analysis of the European Union (EU) and the United States’ (US) AI strategies and considers (i) the visions of a “Good AI Society” that are forwarded in key policy documents and their opportunity costs (ii) the extent to which the implementation of each vision is living up to stated aims and (iii) the consequences that these differing visions of a “Good AI Society” have for transatlantic cooperation.

The authors conclude by comparing the ethical desirability of each vision and identify areas where the EU, and especially the US, need to improve in order to achieve ethical outcomes and deepen cooperation.

Source:

Social Science Research Network (SSRN)

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Article 5:
Sustainability applications for artificial intelligence

Professor Ong Yew Soon (Chief Artificial Intelligence Scientist, A*STAR, President’s Chair Professor of Computer Science, NTU) and Dr. Lim Keng Hui (Assistant Chief Executive Science and Engineering Research Council A*STAR) give their views on how artificial intelligence technologies can be applied to meet the demand for sustainability.

While the use of AI has an impact on CO2 emission and power consumption, it can still provide solutions to reduce one’s carbon footprint and reduce power consumption.

To achieve this, researchers are looking to improve the learning process of the AI by selecting relevant learning models for the algorithm.

Another area of research is neuromorphic computing.

Researchers are trying to apply the workings of the human brain into algorithms to improve them. The lines of research are not limited to improving the algorithms.

They also allow improving the consumption and distribution of natural resources. For this, AI is used in agri-food activities (increasing yields…) or in energy production.

Source:

Sustainability Mag

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Article 6:
7 ways AI could restore trust in public services

Government agencies generate and manage millions of pieces of data annually.

This volume of data multiplies the risk of fraud or misallocation of resources (financial or human). But to curb these problems, the government is deploying AI.

The use of AI will reduce fraud and errors in the tax system and public finances as well as improve the allocation of financial resources.

Another area of improvement will be the detection of fraud in subsidies or the improvement and automation of public services.

But also in the prediction of public health crises. To achieve this, the states are supported by data scientists, civil servants and policy-makers.

Source:

World Economic Forum

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Article 7:
AI in support of the circular economy:
Ethical considerations and a path forward

Since 2018, the use of digital tools (AI, blockchain, robotics, NLP…) for the transition to a circular economy (CE) is growing rapidly.

This is due to the fact that these technologies are capable, either automatically or semi-automatically, to be able to process large volumes of data to make inferences, predictions, generate content and even make decisions in place of human beings.

With the integration of AI in CE, this allows the production and maintenance of circular products.

But also, AI allows developing new business models, to improve recycling structures and processes (sorting, reuse, revalorization).

It is also a better management of energy resources (for example management of consumption in the data center).

The use of AI within the circular economy is not without risk. It brings ethical risks. These risks concern the misuse of private data, the risk of implementing biases in the algorithms.

But also risks of exclusion and economic inequalities as well as environmental risks because of a misuse of AI.

Source:

Social Science Research Network (SSRN)

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Article 8:
Artificial Intelligence for Social Good

“The realization of social good by AI is effective only when the government adequately sets rules for appropriate use of data.”

This report, written by the Association of Pacific Rim Universities (APRU), is a compendium of multidisciplinary studies (philosophy, religion, sociology and technology) carried out by researchers from the Asia-Pacific region (Australia, Korea, Hong Kong, India, Singapore, Thailand).

With their recommendations, the researchers aim to create an enabling environment and governance framework for governments and technology companies.

Contents:

1. Introduction

• Appendix 1: Summaries of Papers and Policy Suggestions;
• Appendix 2: Project History.

2. Philosophical point of view for social implementation

• AI for Social Good: Buddhist Compassion as a Solution;
• Moralizing and Regulating Artificial Intelligence:
  Does Technology Uncertainty and Social Risk Tolerance Matter in Shaping Ethical Guidelines and Regulatory Frameworks?
• Definition and Recognition of AI and Its Influence on the Policy:
  Critical Review, Document Analysis and Learning from Histor.

3. Institutional and technological design development through use of case-based discussion

• Regulatory Interventions for Emerging Economies Governing the Use of Artificial Intelligence in Public Functions;
• AI Technologies, Information Capacity and Sustainable South World Trading;
• Governing Data-driven Innovation for Sustainability:
  Opportunities and Challenges of Regulatory Sandboxes for Smart Cities.

4. How to expand the capacity of AI to build a better society

• Including Women in AI-Enabled Smart Cities:
  Developing Responsible, Gender-inclusive AI Policy and Practice in the Asia-Pacific Region;
• AI and the Future of Work:
  A Policy Framework for Transforming Job Disruption Into Social Good for All

Source:

Association of Pacific Rim Universities (APRU)

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Article 9:
AI4People’s:
7 AI global frameworks

In 2020 AI4People has identified seven strategic sectors (Automotive, Banking and Finance, Energy, Healthcare, Insurance, Legal Service Industry, Media and Technology) for the deployment of ethical AI, appointing 7 different committees to analyze how can trustworthy AI be implemented in these sectors: the AI4People’s 7 AI Global Frameworks are the result of this effort.

AI4People is a grouping created in 2018. It brings together personalities, researchers, industries, media and governmental organizations.

These personalities want to define the principles, practices and policies to build a “good AI society.”

Contents:

Source:

AI 4 People

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