WHAT IS THE PRACTICAL AI ETHICS ALLIANCE?
Every day machines make more and more decisions in our lives. How do we know we can trust those decisions?
We created the AI Ethics Alliance to help bring trust and transparency to artificial intelligence. Most importantly, we’re working towards a practical and implementable AI Ethics system. If your values aren’t implementable then your algorithms will never reflect the essence of your organization.
Practical AI Ethics is hard. Too often the efforts of organizations fall woefully short. Organizations form a committee, issue a report and then nothing changes. Their ideas are just words that don’t translate to anything a data scientist and AI ops engineers can implement in code. With algorithms in charge of critical decisions in people’s lives, from self-driving cars, to deciding who goes to jail, to helping hire and fire people, this old approach cannot stand.
We need a real way to shine light on the decisions machines make. That’s why we’ve created the alliance to bring together ongoing research, tools and people to bring true auditing, transparency and accountability to machine learning.
1) Craft practical AI ethics standards that are actionable for their data science and engineering teams
2) Create a framework for ongoing auditing and management of AI decision making and AI anomalies/errors
3) Outline clear methods for crafting both triage and long term solutions for AI anomalies/errors
4) Train a PR/Customer service team for how to respond to AI errors with customers and the general public
5) Adopt privacy and data sharing policies that protect people’s personally identifiable information
6) Move towards openness with algorithms, datasets and models
7) Develop ethical ways to release or withhold AI technology with dual use potential
8) Outline ways to responsibly report security vulnerabilities with AI systems and models
Alliance Partners are encouraged to join working groups within the Alliance, to further the Alliance’s mission, and to adopt the Alliance’s principals of openness and transparency in their own organizations, and with their customers, at their own discretion.
AI is the future and there’s lots of money to be made from it. But organisations keep making the news over AI governance failings, such as Microsoft’s chatbot that turned racist and google images labelling African-Americans as gorillas. We’re seeing a growth of ethics...
MIT and IBM’s ObjectNet Shows Why Your Image Classifier AI Struggles at Seeing Things in the Real World
No area of machine learning has advanced more rapidly that image classifiers in the past decade. While higher level intelligence has been harder to come by in the world of AI, image recognition feels like a baked technology, with Convolutional Neural Nets dominating...
More and more our devices know where we go, what we do, who we're seeing, our friends and family. Machine learning helps big companies scale their understanding of us but we're only beginning to ask the question, how much do we want companies and nation states...