EthicsNet, a non-profit, is building a community with the purpose of co-creating examples of nice behaviours (such as social norms), to help socialise A.I.
Machine Intelligence requires large, well-documented datasets (examples) to be trained upon. Datasets often matter more than algorithms per se, though they rarely get proper credit for the value that they can create.
Datasets such as Fei-Fei Li's ImageNet have enabled the recent expansion in capability of machine intelligence in powerful new ways that otherwise would be impossible. Bring prosocial requires learning the preferences of others. We need a mechanism to reach those preferences to machines.
We want to do the same for the space of kind behaviours – a massive collaboration efforts to construct, collate, and annotate a range of datasets that reflect many different cultures, opinions and creeds, and which can expand in scope and nuance over time, to empower socially-aware thinking machines for generations to come.
Bring prosocial requires learning the preferences of others. We need a mechanism to reach those preferences to machines.
We recognise that what prosocial behavior looks like varies across time, geography, and culture. We intend to democratize access and opportunity for contribution to this world-changing system, that is currently concentrated in the hand of a few AI researchers/engineers.
Machine intelligences will simply amplify and return whatever data we give them. Our goal is to advance the field of machine ethics, by seeding technology that makes it easy to teach machines about ones individual and cultural behavioral preferences.
Our Massive Transformational Purpose: Help Machines Make Decisions That Enable Flourishing.
EthicsNet is a free and open-source project created as a public good for global society.
Please help us to enable a world with kinder machines.
The intended outcomes of this project are the following:
Empower other, further projects more easily – Seed an ecosystem than can leverage this data, and the means by which it is collected to accelerate developments in this area.
Build a community that can help ensure the project gets taken forward with international collaboration between individuals, companies, and NGOs.
Construct useful dataset(s) that can help to inform machine decision making on prosocial behavior, and the tools required to collect, collate, and annotate it.
Enable cultural contextualization, for increased cultural competence of social machines.
Enable a kind of a 'passport of values' whereby systems can learn ones personal value preferences, an important part of prosocial behavior.