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Blog: ICO and The Alan Turing Institute open consultation on first piece of AI guidance

The following blog relates to the ICO and the Turing's consultation on guidance about explaining the decisions made by AI.

In our co-commissioned citizen jury research, the majority of people stated that in contexts where humans would usually provide an explanation, explanations of AI decisions should be similar to human explanations.

This remains key in the draft guidance, with some sections aimed at those that need summary positions for their work, and others including lots of detail for the experts and enthusiasts.

Our draft guidance goes into detail about different types of explanations, how to extract explanations of the logic used by the system to make a decision, and how to deliver explanations to the people they are about.

Whether you’re a data scientist, app developer, business owner, CEO or data protection practitioner, we want to hear your thoughts.

We will be consulting on this draft guidance until 24 January 2020 and the final version of the guidance will be published later in the year, taking the feedback into account.

Cambridge Centre for Data-Driven Discovery

The Alan Turing Institute: This open community-building event will bring together experts across health, finance, technology, policy, and academia to explore future directions in the digital age for combined health and wealth management.

Public policy

From assisting doctors in the early detection of diseases and supporting scientists who are wrestling with climate change to bringing together diverse groups from around the globe through real-time speech-to-speech translation, AI systems are enabling humans to successfully confront an ever-widening range of societal challenges.

Similarly, in cases where social or demographic data are being used as inputs in AI decision-support systems—for instance, in domains such as criminal justice, social care, or job recruitment—the employment of ‘black box’ models leaves designers and deployers no way to properly safeguard against possibilities of lurking biases that may produce inequitable or discriminatory results.

In order to manage the impacts of AI responsibly and to direct the development of AI systems toward optimal public benefit, The Alan Turing Institute's public policy programme partnered with the Office for Artificial Intelligence and the Government Digital Service to produce guidance on the responsible design and implementation of AI systems in the public sector.  The guide, Understanding Artificial Intelligence Ethics and Safety, is the most comprehensive guidance on the topic of AI ethics and safety in the public sector to date.

The guidance is relevant to everyone involved in the design, production, and deployment of a public sector AI project: from data scientists and data engineers to domain experts, delivery managers and departmental leads. Our aim -- and hope -- in writing the guide is to encourage civil servants interested in conducting AI projects to make considerations of AI ethics and safety a first priority.

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