guidelines
Closing the AI accountability gap: defining an end-to-end framework for internal algorithmic auditing
Research
In this paper, we introduce a framework for algorithmic auditing that supports artificial intelligence system development end-to-end, to be applied throughout the internal organization development life-cycle...
guidelines
The Ethics of AI Ethics – An Evaluation of Guidelines
Research
Current advances in research, development and application of artificial intelligence (AI) systems have yielded a far-reaching discourse on AI ethics. In consequence, a number of ethics guidelines have been released in recent years. These guidelines comprise normative principles and recommendations aimed to harness the “disruptive” potentials of new AI technologies...
guidelines
From What to How: An initial review of publicly available AI Ethics Tools, Methods and Research to translate principles into practices
Research
The debate about the ethical implications of Artificial Intelligence dates from the 1960s. However, in recent years symbolic AI has been complemented and sometimes replaced by Neural Networks and Machine Learning techniques. This has vastly increased its potential utility and impact on society, with the consequence that the ethical debate has gone mainstream. Such debate has primarily focused on principles - the what of AI ethics - rather than on practices, the how. Awareness of the potential issues is increasing at a fast rate, but the AI community's ability to take action to mitigate the associated risks is still at its infancy. Therefore, our intention in presenting this research is to contribute to closing the gap between principles and practices by constructing a typology that may help practically-minded developers apply ethics at each stage of the pipeline, and to signal to researchers where further work is needed. The focus is exclusively on Machine Learning, but it is hoped that the results of this research may be easily applicable to other branches of AI. The article outlines the research method for creating this typology, the initial findings, and provides a summary of future research needs...
guidelines
On Artificial Intelligence – A European approach to excellence and trust
European CommissionRecommendations
On 19 February 2020, the European Commission published a White Paper aiming to foster a European ecosystem of excellence and trust in AI.
guidelines
Leading your organization to responsible AI
Mckinsey & CompanyPrinciples & Guidelines
Company values can offer a compass for the appropriate application of AI, but CEOs must provide employees with further guidance...
guidelines
Microsoft AI principles
MicrosoftPrinciples & Guidelines
We put our responsible AI principles into practice through the Office of Responsible AI (ORA) and the AI, Ethics, and Effects in Engineering and Research (Aether) Committee. The Aether Committee advises our leadership on the challenges and opportunities presented by AI innovations. ORA sets our rules and governance processes, working closely with teams across the company to enable the effort.
guidelines
How do you teach AI the value of trust?
Ernst & YoungPrinciples & Guidelines
EY developed a trusted AI framework to help enterprises understand the slate of new and expanded risks that may undermine trust not only in these systems, but also in products, brands and reputations...