  This paper plans to develop an Equitable and Responsible AI framework with
enabling techniques and algorithms for the Internet of Energy (IoE), in short,
RAI4IoE. The energy sector is going through substantial changes fueled by two
key drivers: building a zero-carbon energy sector and the digital
transformation of the energy infrastructure. We expect to see the convergence
of these two drivers resulting in the IoE, where renewable distributed energy
resources (DERs), such as electric cars, storage batteries, wind turbines and
photovoltaics (PV), can be connected and integrated for reliable energy
distribution by leveraging advanced 5G-6G networks and AI technology. This
allows DER owners as prosumers to participate in the energy market and derive
economic incentives. DERs are inherently asset-driven and face equitable
challenges (i.e., fair, diverse and inclusive). Without equitable access,
privileged individuals, groups and organizations can participate and benefit at
the cost of disadvantaged groups. The real-time management of DER resources not
only brings out the equity problem to the IoE, it also collects highly
sensitive location, time, activity dependent data, which requires to be handled
responsibly (e.g., privacy, security and safety), for AI-enhanced predictions,
optimization and prioritization services, and automated management of flexible
resources. The vision of our project is to ensure equitable participation of
the community members and responsible use of their data in IoE so that it could
reap the benefits of advances in AI to provide safe, reliable and sustainable
energy services.
