To provide relevant and reputable global ethics resources to discerning AIS stakeholders that work on improving the future of humanity with ethical behavior considerations.


Ethics is a broad domain of moral principles that can help guide human and technology behavior.  In this context, AI (artificial intelligence) and AIS (autonomous intelligence systems) ethics refers to the ethics of technology that concerns the moral behavior of humans as they design, construct, and use AI and the behavior of AIS at it impacts the world and humanity.


This portal is for people that want to work on AIS projects that move ethical considerations beyond the abstract to action oriented, beyond principles to practice. We aim to provide a portal where the coordination of AIS ethics can begin to ideate with access to a global database of relevant and reputable resources in one place.


Read detailed definitions of AI and AIS below. For simplicity, the acronym AIS is used most often in lieu of AI/AIS to decrease redundancy. 


This is a BETA test site, a MINIMAL VIABLE PRODUCT that serves as an example of one possible direction (of many) in global AIS ethical thinking, research and education. We wish to help stakeholders move from superficially reviewing long lists of experts, and hundreds of private, public, and NGO principles, guidelines, codes, and legal regulations, now available globally and continuously expanding daily. We want to help move from reading lists with URL’s to offering vetted qualified AIS resources based on an ethically designed, open, transparent, responsible and rigorous selection process.



To provide a growing set of evidence-based global ethics resources in the field of AIS ethics using a unified framework of relevant and reputable sourcing (Floridi & Cowles, 2019).  We use unified framework based on the transparent reporting of systematic reviews, meta-analyses and critical evaluation. Our PRISMA method (adapted from the medical domain) and process of selection of these resources aims to be:

  1. ETHICALLY DESIGNED – from the design of the format of this portal to its contents and ingredients; we aim to think, act, and create resources for others with ethical considerations in mind.
  2. OPEN – we will be making provisions for open feedback and collaboration and coordination both in format and substance.
  3. TRANSPARENT – the criteria used to select each resource data point will be made open and available for critical evaluation.
  4. RIGOROUS – we will make every effort to include rigor in our systematic review, meta-analyses and critical evaluations of resources selected for the portal


AI (artificial intelligence)

We use the European Commission’s definition for AI:
“Artificial intelligence (AI) refers to systems that display intelligent behaviour by analysing their environment and taking actions – with some degree of autonomy – to achieve specific goals. AI-based systems can be purely software-based, acting in the virtual world (e.g. voice assistants, image analysis software, search engines, speech and face recognition systems) or AI can be embedded in hardware devices (e.g. advanced robots, autonomous cars, drones or Internet of Things applications).”

AIS (artificial intelligent systems)

In agreement with the AI HLEG (2019); we use the term AIS to mean any AI-based component, software and/or hardware (whether embedded or stand alone). The term AI contains an explicit reference to the notion of intelligence. But because intelligence (both in machines and in humans) is a dynamic concept, although it has been studied at length by psychologists, biologists, and neuroscientists, AI engineers, practitioners, and AI researchers use it mostly to refer to the notion of rationality. In other words, the ability to choose the best action to take in order to achieve a certain goal, given certain criteria to be optimized and the available resources. Rationality is not the only ingredient in the concept of intelligence, but it is a significant part of it.

Floridi, L., & Cowls, J. (2019). A Unified Framework of Five Principles for AI in Society. Harvard Data Science Review. https://doi.org/10.1162/99608f92.8cd550d1

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