This chapter considers the contributions that may be made to the evolution of an ethical and compassionate form of artificial general intelligence (AGI) by integrating knowledge graphs for classical economics, education, health, and space science. Classical economics offers pathways to the evolution of a form of AGI characterised as moral, ethical, and providing a capacity for building trust-based social capital of societies. Pathways that can be elucidated by applications of machine and deep learning to knowledge graphs of the fields of classical economics, ethics, and social capital. A network platform based on the application of distributed ledger technology is proposed to provide the basis for eliciting insights from interdependences between an ever expanding digital-quantum cloud hosting similarly empowered knowledge graphs for an ever increasing myriad of advancing fields. Knowledge graph sketches for education, health, space science, and other fields germane to building social capital serve to illustrate this proposed process and attendant business opportunities.
TopIntroduction
Goertzel (2020), one of the world’s leading developers of software and robots seeking to achieve Artificial General Intelligence (AGI), visualises at least three plausible scenarios for the evolution of AGI:
- 1.
“Corporate Techno-Fascism” leading to “a dark future of corporate-totalitarian hegemony”;
- 2.
Decentralised-Digital-Democracy (DDD) leading to “a future of diverse flourishing creativity”;
- 3.
“Human Free” leading to “a future in which advanced AGI tech leaves biological humanity entirely by the wayside”.
In chapter 3 the author refers to decentralisation and digitalisation of remote, rural, and regional communities worldwide. By harnessing breakthroughs in AI-based technology and business opportunities these communities could become increasingly capable of establishing and operating their own processes in the target sectors of food production, education and healthcare achieving high levels of self-sufficiency and resilience post-covid-19. MacDonald & MacRae (2019) also consider AI-based building of social capital focussed on reducing inequality in target sectors for housing, employment and belonging – DDD leading to “diverse flourishing creativity”.
To maximise benefits, AI could be trained to not only determine the effective utilisation of technology to achieve high levels of self-sufficiency and resilience in the target sectors but also in so doing develop an understanding of and empathy with human desires to achieve such outcomes. Chapter 3 proposes further AI advances within the sectors while this chapter offers a view of how AI in progressing towards AGI can be directed towards fulfillment of the latter. This view also considers how to minimise the threats of Goertzel’s dark options of unimpeded “corporate techno-fascism” and “human free” sidelining.
First up is an annotated list of organisations guiding the evolution of benevolent AI. Consideration then turns to a platform to integrate Knowledge Graphs (KGs) using distributed ledger technology (DLT) such as blockchain. KGs can be constructed from a knowledge base of entities and the relationships among them. Perhaps the World Bank (2018) has published the most concise DLT definition:
Distributed ledgers use independent computers (referred to as nodes) to record, share and synchronize transactions in their respective electronic ledgers (instead of keeping data centralized as in a traditional ledger).
The integration of KGs involves exchanging insights and facts stimulated by requests between KGs that are DLT facilitated, accountably and securely. Analytical techniques such as machine learning (ML) and its subset deep learning (DL) encompassing artificial neural networks (ANN) can generate insights and extract or abstract new facts from the content of KGs. Beyond the current focus in the AI world on advancing and using these powerful analytical techniques, applications are proposed to filter exchanges for trustworthiness (encompassing authenticity, logic, and empathy), truthfulness, adherence to codes of ethics, common sense, causality, the need to negotiate terms of exchanges, and rating the efficacy and impact of the exchange of insights and new facts. Applications of APIs are proposed to transform the content of a request for exchange and/or the response to the exchange in forms comprehensible to the respective KGs.
Consideration is then given to the formulation of guiding KGs describing pathways to the attainment of global well-being. These would be available to operate on request as a guide to the processes of formulating and developing KGs. Early candidates for guiding KGs, sketched only in the following, consider roles for AI in generating insights and extracting or abstracting new facts from building trust-based social capital, reinvesting in classical economics and the contributions of leaders in AI.
Finally, consideration is given to the formulation of KG sketches designed to explore AI inspired pathways to achieving post-covid self-sufficiency and resilience in education and health of remote, rural and regional communities worldwide. Emerging roles for AI in outer space and their interplay with the foregoing is also outlined in a final KG sketch.
Organisations Guiding The Evolution of Benevolent AI
Many public institutions and private sector organisations have been established to regulate, guide, and assess the rapidly increasing growth in the application of AI.