3.2 Socio-humanitarian artificial intelligence
Digitalization is changing managerial approaches, organisational architectures and personal interactions. Strong innovation rates...
A Socio-humanitarian environment and a collective intelligence phenomenon make new demands on artificial intelligence (AI). Traditional AI can only recognize, predict, and answer relatively simple questions. However, thinking, understanding, explaining and dealing with complex problems is not available to current AI, which cannot harness the meaning of what this relationship implies. Only humans can understand ideas of the universe and possess consciousness of the holistic micro- and macro-worlds. Collective intelligence is immersed into an unconscious space. A person is able to make correct and at the same time uncaused decisions. Humans have intuition, can meditate and fall into a trance. The events depend on the observer and AI behaviour has to take into account the collective human observers. These events integrating human and AI become a part of a hybrid reality with fuzzy boundaries.
Interactions between socio-humanitarian environment and AI create caused and uncaused complete loops of observing/deciding/acting/ learning processes with its elements and services. Non-formalizable cognitive functions begin to play an important role. The collective behaviour of people and AI systems activities, by conciliating both technological and cognitive approaches, may proceed in opposite directions. The first one proceeds top-down from non-formalizable uncaused and chaotic human consciousness towards purposeful and sustainable human-machine interactions. The second is based on logical-formalizable and multi-agent architectures that are carried out bottom-up from tiny, intelligent machines towards high-end computing. It results in a framework for copying with dualities of different models in Hybrid Strong Artificial Intelligence (HSAI).
Traditional AI helps to perform routine operations. Only a few researchers are arguing that AI can copy emotions and thinking processes by logical means. The general and strong AI moves further into the areas previously inaccessible for understanding people´s capabilities: the collective unconscious, the transcendental state of mind. Unlike traditional AI, HSAI enables acting in the unlimited real world. It possesses capacities to sense, reason and understanding. It can set the purposes and are being monitored themselves through time-space limitation to the benefit of humans with continuous revision of goals and even stay an actor when goals are absent.
To build HSAI the paradigm of AI development has to undergo changes. It is necessary to include an observer into the system of AI, i.e., a person who actively, reflexively and cognitively influences a socio-humanitarian situation. This inclusion can make the problem-solving inverse, unsustainable, non-logical. Instead of a traditional logical or neuro-network AI, apparently, it is necessary to dive down to the atomic or rise onto relativistic levels, to achieve adequate semantic interpretation of AI models. The power of HSAI maybe 30-50 orders of magnitude higher than the traditional AI.
Advanced AI technologies are useful for group strategic formation for self-organising social networks, rising social responsibility, and creating effective plans for government, non-government, regional, national, municipal, and other bodies. But there is a high risk of societal development with limited attention to people´s emotions, lacking soul. All of this can lead to a sharp reduction in jobs, and as a consequence, social unrest. Due to HSAI development, the malicious use of AI can be dangerous on local and on an international scale.
This session aims to discuss such ideas and propose disruptive AI development solutions in the present and future.
AI implementation issues in the social and humanitarian sphere
AI-accelerating advanced and networked democracy processes
AI-powered social responsibility in Hybrid Reality
The issue of integrity in collective and artificial intelligence
Time-, space-, boundary-limitations of HSAI
Architectures and frameworks of HSAI
Ethical approaches to counteract malicious use of AI