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Practical Ethics: Eleven Standards for Engineering Ethics into the Design of Intelligent Systems

Increasingly we hear about algorithms that shape our everyday lives. They are trained on data, evolve with data, make descisions based on data. Lots of this data is human data transformed into mathematical forms and digits. The development of our data processing systems points toward even more and intenser data processing with more and more “intelligently” acting software that define everything from our politics to economy and culture.

The ethical implications are tenfold when intelligent systems e.g. start replicating our human bias, profiling individuals and predicting and acting upon their life trajectory. We see that these systems are not just objective mathematical systems, they are social systems that represent, reinforce interests power relations and create or limit opportunities for individuals.

A great element of the sollution lies in the engineering and design of the systems. But how to?

The worlds’ largest organisation for engineers IEEE started a few years ago the Global Inititiative on Ethics of Autonomous and Intelligent Systems with the objective to:

ensure every stakeholder involved in the design and development of autonomous and intelligent systems is educated, trained, and empowered to prioritize ethical considerations so that these technologies are advanced for the benefit of humanity.”

The first result of the cooporation of hundreds of thought leaders from academia, science, government and corporate sectors in the fields of Artificial Intelligence, ethics, philosophy, and policy all over the world is the Ethically Aligned Design paper version 1 and 2.

But in addition eleven engineering standards working groups have been formed:

P7000 – Model Process for Addressing Ethical Concerns During System Design

P7001 – Transparency of Autonomous Systems

P7002 7002 – Data Privacy Process

P7003- Algorithmic Bias Considerations

P7004 Standard for Child and Student Data Governance

P7005 Standard for Transparent Employer Data Governance

P7006 Standard for Personal Data Artificial Intelligence (AI) Agent

P7007 Ontological Standard for Ethically Driven Robotics and Automation Systemsma

P7008 Standard for Ethically Driven Nudging for Robotic, Intelligent and Autonomous Systems

P7009 Standard for Fail-Safe Design of Autonomous and Semi-Autonomous Systems

P7010 Wellbeing Metrics Standard for Ethical Artificial Intelligence and Autonomous Systems

The journalist Daniel Faggella has made a great overview of the 11 standards, their core work, and asked the people involved in the initiative some great questions with direct relevance to business leaders: Which types of businesses should consider using to your standard, and why? (i.e. Why are these standards relevant to business people now?) and What would adherence to this standard look like in a real business setting? Read the answers here (including DataEthics’) in his article The Ethics of Artificial Intelligence for Business Leaders – Should Anyone Care? in TechEmergence