Trustworthy AI results from how people, processes and technologies function together across multiple dimensions of trust. Not every dimension is pertinent for every organization or cognitive tool. Rather, the dimensions of trust are lenses for interrogating AI design, function, and outcomes. With regular activities, decisions and documentation across the AI lifecycle, weighing and addressing the dimensions of trust is what permits effective AI governance and unleashes AI’s greatest potential value. These dimensions are explored in depth in Trustworthy AI, by Beena Ammanath.
As we deploy machines that can perform analysis and even make decisions on our behalf, we require confidence that the machine intelligence is fair and impartial in its outputs. The challenge of course is that AI cannot “think” or “reason.” The onus falls on human stakeholders to probe how an AI functions relative to expectations for fairness and concerns over bias.
When AI outputs are inconsistently accurate, the result is uncertainty, and when models function as intended only within narrow and limited use cases, trustworthiness can suffer in other applications. Data scientists are challenged to build provably robust, consistently accurate AI models in the face of changing real-world data, and by this, two vital compon…
There is growing awareness worldwide around how AI application can impact the privacy concerns of citizens, organizations and governments. Privacy in AI relates to guarding sensitive information, gaining consent for use of that data, ensuring models do not divulge protected data, using models in a way that respects privacy, and meeting emerging laws and regulations around…
Our trust in powerful AI that can change every industry requires systems that can be secured against a variety of threats, many of which are not yet imagined, much less manifest. The path forward requires an awareness of how AI tools may become compromised, the implications from it, and plans and processes to keep security at the forefront of strategy…
A cross-cutting dimension that impacts all other aspects of ethical AI is transparency. It permits accountability, motivates explainability, reveals bias, and encourages fairness. With sufficient transparency, datasets are understood, algorithms can be traced back to their training data, and deployed solutions are understood to be accurate (or not).
Despite their power and potential, AI tools are still just mathematical models. What happens when an AI makes a decision with a negative impact on an individual or organization? The model itself cannot face any real consequence. Instead, accountability for AI and responsibility for deciding when and how it should be used is a uniquely human…
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. ..
Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book.
Trustworthy AI results from how people, processes and technologies function together across multiple dimensions of trust. Not every dimension is pertinent for every organization or cognitive tool.These dimensions are explored in depth in Trustworthy AI, by Beena Ammanath.
Beena Ammanath is a global thought leader in AI ethics and an award-winning senior technology executive with extensive global experience in AI and digital transformation. Her work has spanned leadership roles in e-commerce, finance, marketing, telecom, retail, software products, service, and industrial domains. She is the Executive Director of the Global Deloitte AI Institute…
Beena Ammanath is a global thought leader in AI ethics and an award-winning senior technology executive with extensive global experience in AI and digital transformation. Her work has spanned leadership roles in e-commerce, finance, marketing, telecom, retail, software products, service, and industrial domains. She is the Executive Director of the Global Deloitte AI Institute and leads Trustworthy AI and Ethical Technology at Deloitte. Prior to joining Deloitte, Beena served as the CTO for AI at Hewlett Packard Enterprise, where she created a new practice area focused on AI and emerging technologies. Before this, she was the head of Data Science and Innovation at General Electric, working across all GE businesses, including aviation, transportation, healthcare, power, energy and renewables, and oil and gas…
There has arguably never been a more exciting time in AI. Alongside the arrival of so much promise and potential, however, more attention is due to the ethics and trustworthiness of this powerful technology. It is a question of not just what can be done with AI but how it should be done – or whether it should be done at all. Because AI has been developed to this level of maturity, we must now grapple with some of the more complex ethical considerations concerning AI.
What does it mean for AI use to be ethical? How do we know if we can trust the AI tools we use?
The trajectory of AI can be conceived along three streams: research, application, and trust and ethics. Research concerns data science…
Businesses today are rapidly scaling AI to gain powerful new capabilities and to improve how they operate. Humans and machines are increasingly working together. And this trend exposes businesses to heightened risk of AI behaving in ways that are unethical. Just like their human counterparts in the workforce, AI systems are expected to adhere to social norms and ethics and to make fair decisions in ways that are consistent, transparent, explainable, and unbiased. Of course, figuring out what is ethical and socially acceptable isn’t always easy – even for human workers…
Businesses today are rapidly scaling AI to gain powerful new capabilities and to improve how they operate. Humans and machines are increasingly working together. And this trend exposes businesses to heightened risk of AI behaving in ways that are unethical. Just like their human counterparts in the workforce, AI systems are expected to adhere to social norms and ethics and to make fair decisions in ways that are consistent, transparent, explainable, and unbiased. Of course, figuring out what is ethical and socially acceptable isn’t always easy – even for human workers.
Trustworthy AI offers readers a pragmatic and direct approach to ethics and trust in artificial intelligence. The book presents a straightforward and structured way to think about AI ethics and offers practical guidelines for organizations developing or using AI solutions.
今日の企業は、強力な新機能の獲得と業務改善のために AI を急速に拡大しています。人間と機械の連携がますます進んでいます。そしてこの傾向により、企業は AI が非倫理的な行動をとるリスクが高まっています。職場の人間と同じように、AI システムも社会規範と倫理を遵守し、一貫性、透明性、説明可能性、偏見のない方法で公正な決定を下すことが求められています。もちろん、倫理的で社会的に許容されるものを判断するのは、人間の労働者にとっても必ずしも簡単ではありません。
『Trustworthy AI』は、人工知能の倫理と信頼に対する実際的かつ直接的なアプローチを読者に提供します。この本は、AI 倫理について考えるための単純かつ構造化された方法を示し、AI ソリューションを開発または使用する組織に実用的なガイドラインを提供します。
今日の企業は、強力な新機能の獲得と業務改善のために AI を急速に拡大しています。人間と機械の連携がますます進んでいます。そしてこの傾向により、企業は AI が非倫理的な行動をとるリスクが高まっています。職場の人間と同じように、AI システムも社会規範と倫理を遵守し、一貫性、透明性、説明可能性、偏見のない方法で公正な決定を下すことが求められています。もちろん、倫理的で社会的に許容されるものを判断するのは、人間の労働者にとっても必ずしも簡単ではありません。
『Trustworthy AI』は、人工知能の倫理と信頼に対する実際的かつ直接的なアプローチを読者に提供します。この本は、AI 倫理について考えるための単純かつ構造化された方法を示し、AI ソリューションを開発または使用する組織に実用的なガイドラインを提供します。
