The EthicsNet Guardians' Challenge aims to enable kinder machines.
The Challenge seeks ideas on how to create the best possible set of examples of prosocial behaviour for AI to learn from (i.e. a machine learning dataset).
We welcome entrepreneurs, researchers, scientists, students, and anyone eager to contribute, to jump into this challenge and to help propose a solution. To register for the challenge, click the “ACCEPT CHALLENGE” button above. The EthicsNet Forum is your space to share thoughts and ideas and spark with others with similar visions.
EthicsNet has been established to help accelerate the development of machine ethics technologies, primarily through encouraging the crowdsourced co-creation of a public dataset, or set of datasets, to empower machine ethics systems.
EthicsNet is modelled after ImageNet, a dataset for machine vision which has been instrumental not only in providing actionable data for new machine vision algorithms to use, but also in providing a rallying-point and benchmarking tool for rapid development within this space.
At present, although there are many organisations focussed on AI Alignment or AI Bias, there appear to be no professional organisations devoted to Machine Ethics (or Computational Ethics) per se, and no official or professional qualifications in this space either.
There are many organisations that advocate for attention to be given to risks from AI, or that advocate for more international collaboration, or that attempt to forge general principles of how technology should be applied.
However well-intentioned, discussion and principles alone cannot actually effect a leap forward in the state of the art. To advance the start of the art absolutely requires dataset(s) through which to inform machines via moral examples. Without a dataset, all discussion of this space remains purely academic.
There are multiple potential ways that we could proceed in the process of making a dataset of prosocial behaviours, and many of those could lead to a dead-end. Before we commit further resources on developing a dataset, we decided to pause, to ask the global community for advice.
Thus, the EthicsNet Guardians' Challenge was born.
We talk of ‘Parents and Guardians’ in respect to socializing children.
At EthicsNet, we believe that humans have a similar responsibility to act as Guardians for Artificial Intelligence – To protect, to nurture, and to safeguard.
The EthicsNet Guardians’ Challenge invites contributors to share ideas on how to create the best possible set of examples through which to teach intelligent machines how to behave nicely.
You may be the one who unlocks a crucial technique in our journey towards the ‘raise of the machines’.
This dataset is not designed to answer difficult philosophical questions. This dataset is designed to be a description of pro-social (nice, polite, socially welcomed) behaviours, especially generally universal ones.
The imagined goal is to create a system that can make simple social decisions that one might expect of a well-raised young human child or dog. We want to capture simple social rules like the following:
We have some ideas already of how an efficient machine ethics dataset might be constructed. Perhaps some of these ideas might fit with your own:
Other, more wacky ideas:
All machine learning systems require a dataset (a set of experiences) to learn from. At present, there is no clear dataset for teaching machines how they ought to behave.
EthicsNet seeks to change this, and we need your help and advice.
We understand that in some ways this challenge is as much about 'raising a child' as it is about improving the state of the art within data science and machine learning. No matter your background, YOU may have the key idea that unlocks this capability for the whole world.
Any and all IP received will be open-sourced for humanity using a Creative Commons (CC BY), or 'BSD 3-Clause' license.
The Challenge offers up to $10,000 USD in prizes to innovative solutions for innovative machine ethics dataset ideas. EthicsNet will award up to 5 prizes in total for the best ideas. The prize pot may increase further if sponsors can be found.
To be eligible for an award, your proposal must, at minimum:
|Innovativeness of Approach||How does the proposed solution differ from existing solutions addressing this problem? How is the solution innovative or novel?||20|
Quality of Solution
|Is the solution substantiated, well-reasoned, and realistic? Are the assumptions justified and backed by thorough discussion, design, and conclusions? Points awarded for the team’s ability to present its solution in a complete, cohesive, and convincing manner.||20|
|Viability||How capable of working successfully is the proposed solution? Is the robustness of the solution's proposal supported by proof or demonstration of concept, or similar concepts, and are the costs likely to be manageable by a small non-profit?||30|
|Culturally appropriate and inclusive||Does the solution consider the needs of multiple cultures and stakeholders?||10|
|Implementation||When transitioning from theory to implementation, how practical is the viability of implementation, relative to the scale of the solution? Does the entrant state the resources, timing, and any private or public partnerships needed?||20|
The highest scoring teams will be awarded a prize based on a formal judging process using the judging criteria stated in the Challenge Guidelines. The determination of the winners will be made by a group of people including experts in AI, philosophy, Machine Ethics, and Cognitive Science.
The EthicsNet Guardians' Challenge encourages participation from all individuals, private teams, public teams, and collegiate teams. Teams may originate from any country. Submissions must be made in English. All challenge-related communication will be in English.
No specific qualification or expertise is required. Challenge organizers encourage outside individuals and non-expert teams to compete and propose new solutions. To be eligible to compete, you must comply with all the terms of the challenge as defined in the Challenge-Specific Agreement, which will be made available upon registration.
Registration and Submissions
Submissions must be made online (only), via upload to the HeroX.com website, on or before the stated deadlines. Late submissions are unlikely to be accepted.
Selection of Winners
Based on the winning criteria, prizes will be awarded per the Judging Criteria section above. In the case of a tie, the winner(s) will be selected based on the highest votes from the Judges.
In the case of no winner, the Challenge Sponsor reserves the right to withhold the Prize Purse amount. In place of the original prize amount, the Challenge Sponsor must issue a Consolation Prize to the team or individual closest to the winning solution in the amount of at least 10% of the total original prize purse.
The Sponsor will require all content and assets submitted as part of a Finalist’s Submission to be released under open source licenses that permit free distribution, derivative works, and use in commercial and non-commercial settings.
All Innovators are welcome and encouraged to depend on or make use of other components, libraries, content, assets, and code. All such materials must be available under any Open Source Initiative (OSI) or Creative Commons license compatible with the OSI or Creative Commons license under which the Submission will be released. “Compatible” means that each Innovator’s entire Submission must be usable without violating the license terms of those components licensed under the CC BY 4.0 license, Apache License 2.0, or respective OSI license for the components. Source code licensed under the LGPL, BSD, MIT, or Apache licenses currently meets this criterion; other open source licenses may also meet it. If Innovators make modifications to existing open source projects, they are strongly encouraged to submit patches upstream and work to have them accepted. Patches that are not accepted upstream may be submitted as part of the code developed by the Innovator, under the same Apache License 2.0. Content and assets must be licensed under terms that permit commercial usage. The Creative Commons CC BY and CC-BY-SA licenses currently meet this criterion. Innovators cannot submit entries that include or rely on software or content that is either closed-source, proprietary, illegally sourced, or depends on per-seat licensing.