EthicsNet Launches Crowdsourcing Competition to Enable Kinder Machines
EthicsNet, a non-profit building a community dedicated to co-creating a dataset of pro-social behaviour for machine ethics algorithms, has recently launched the EthicsNet Guardians’ Challenge. This crowdsourcing competition welcomes entrepreneurs, researchers, scientists, students, and all AI enthusiasts to share ideas on creating the best possible machine learning dataset.
June 27, 2018
EthicsNet is pleased to reveal the launch of the EthicsNet Guardians’ Challenge. A non-profit with the vision to further the advancement of the rapidly emerging domain of Machine Ethics, EthicsNet is looking to build a community that will work together towards creating a dataset for machine ethics algorithms. Through the Guardians’ Challenge, they are inviting contributors to share ideas on creating the best possible dataset that will teach intelligent machines to behave kindly.
Human interactions with intelligent machines have evolved rapidly in the recent years to become closely interweaved. However, experts suggest that trust is an integral factor to enjoy the benefits of AI. EthicsNet believes that consistent behaviour over time is an important aspect of trust. They also believe that humans must interact with intelligent machines as they do with their children and pets, teaching them how to behave appropriately in any given circumstance.
EthicsNet follows in the path of the highly successful ImageNet dataset that has revolutionised Machine Vision technologies in recent years.
“We have an opportunity to teach machines to be friendly and kind, just like well-raised children. However, we need a ‘storybook’ to teach them from. This Challenge asks about the best way to create those examples,” says Nell Watson, founding Chair of EthicsNet.
The term Machine Ethics refers to a wide range of techniques capable of helping machines make decisions in a socially acceptable manner. EthicsNet was founded with the objective to develop state-of-the-art machine ethics technologies via crowdsourced co-creation of a public dataset. The company has been modelled after ImageNet, a dataset for machine vision that provides actionable data for new machine vision algorithms as well as a benchmarking tool for development.
“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,” explains Nell Watson, faculty of AI at the reknowned Singularity University, and a founder of EthicsNet. “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.”
EthicsNet is looking to leverage the power of the crowd to find the right idea that will pave the way for creating an ideal dataset for machine ethics. The interested participants can sign-up for the challenge by visiting https://www.herox.com/EthicsNet
More about EthicsNet can be found at https://www.ethicsnet.com/
About EthicsNet: EthicsNet, a non-profit, is building a community with the purpose of co-creating a dataset for machine ethics algorithms. Their goal is to advance the field of machine ethics, by seeding a framework for analysis of various ethical situations, in a way that can be easily understood by both humans and machines. Through their dataset, EthicsNet seeks to support new ways of expressing ethics computationally, building on the latest and best available research.