Essay

Motivation is the process that initiates, guides and maintains goal-oriented behavior while wisdom represents the highest level of intelligence one could be motivated to achieve.

Wisdom resists automatic thinking and grasps a deeper meaning of what is known but also understands the limits of knowledge. Hence, enhancing Artificial Intelligence (AI) with Artificial Wisdom (AW) will open new conceptual models for reaching human-level AI.

The design principles for AW-systems are in line with the ongoing paradigm-shift in AI-research, moving from a deterministic massive data-driven, pattern-recognition model to a human-learning model.

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Self-reflection is a process of communicating internally with oneself. Sensing and recording of this process provides a means for developing an intelligent  ‘robot’ that mirrors our own life experiences, interacting with the outside world similar to the way a child learns.

Realtime sensing of behavioral and physical body data is rapidly advancing. The primary design-goal of this ‘robot’ is to support humans to overcome limits of learning and to provide support in the decision-making process. 

Motivation and purpose have to remain the driving authority that controls this process. How much authority we want to give these ‘assistants’ in carrying out specific tasks is up to us, respectively the organization engaged in AI-supported automation.

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While Digital-Transformation is setting the stage for moving on to AI-Transformation it appears that many corporations are struggling in realizing its potential benefits. 

To master the increasing complexity produced by advances in AI-research and its impact on  AI-Transformation demands a corporate culture that supports these changes at all levels.

Collaboration is the key in mastering the raising complexity of science and technology. Most importantly collaboration is a prerequisite for collective intelligence, the Nr.1 success factor in mastering corporate complexity and likely the future benchmark for ‘survival-of-the-fittest’.

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While the EQ has gained in importance with intelligent machines gradually replacing cognitive tasks, a new ‘AIQ’ will provide guidance to optimally “cross the bridge” between artificial and human intelligence.

With this bridge in place, we can test and compare our true thinking capacity with artificially computed results. Doing so, we must understand the limits and advantages of the artificial version as much as we need to understand the limits of our own personality.

Hence, in addition to IQ und EQ, a newly defined AIQ is required for testing one’s creativity and ability for assessing the solution proposed by the AI system. Introducing the AIQ requires an adjustment of our educational concepts with creativity as its main driver.

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Brain-Computer-Interfaces (BCIs) read and interpret brain activity. To handle the massive influx of data, AI is used to detect neural patterns and provide feed-back.

At the 2017 World Government Summit, Elon Musk suggested that humans should merge their biological-intelligence with machine-intelligence to enhance their cognitive and sensory abilities, fighting-off the supremacy of future super intelligent machines.

To prevent misuse, tough legal constraints need to be enforced to regulate the potentially positive as well as the potentially negative implications of neural augmentation. Considering what has become reality from past dystopian visions as suggested by Huxley and Orwell, there are good reasons to be alarmed.

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According to Kahneman’s theory, human decisions are supported by two different kinds of mental abilities: a thinking pattern (‘system 1’) providing tools for intuitive and often unconscious decisions and a second pattern (‘system 2’) handling more complex situations.

Viewed by Neuroscience, an emotional response in decision-making triggers the question how the brain can coordinate the fast thinking of Kahneman’s system 1 with the slow thinking of system 2?

A hybrid AI-system, combining ML with Symbolic AI, offers an intriguing possibility to draw a parallel between the mental mindsets represented by Kahneman’s system 1 and system 2. This implies that future AI-system could be based on a hybrid multi-agent architecture where an individual agent focuses on specific skills and problems to be solved.

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Awareness is growing that human self-reflection and spirituality can be a vital resource in solving today’s global problems, challenging the role of AI as the single source of new knowledge.

The links of our spirituality to our intelligence and its conduits to the biological, neural sphere are not yet fully understood, but scientific enquiry oriented to enhance the biological in humans and replicating it in machines is growing exponentially.

Historically, nature, mountains, rivers, trees, the sun, the moon have always been honoured in ancient cultures as a source of enlightenment. Expanding our awareness about nature, with AI as a tool, might well support our endeavour of leading a meaningful life.

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Surveillance capitalism is an economic system centred around the commodification of personal data with the core purpose of profit-making.

In her latest book ‘The Age of Surveillance Capitalism’ Shoshana Zuboff, Professor at Harvard, provides a detailed examination of the unprecedented power of surveillance capitalism and the quest by powerful corporations to predict and control our behaviour. In her view industrial capitalism exploited nature while surveillance capitalism now exploits human nature.

The stronger personal autonomy is, the more fulfilled and productive a human being may become in adapting to today’s socioeconomic demands. Hence, a mindset of personal autonomy is fundamental vis-à-vis the potential negative impacts of surveillance capitalism.

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To understand the complexity of achieving AGI it is worthwhile looking at some of the capabilities that AGI will need to master such as sensory perception, natural language understanding, creativity, and social and emotional engagement.

Brain processes underly not only simple motoric behaviours such as walking and eating but also complex cognitive acts and behaviour that we regard as basically human: thinking, speaking and creating works of art.

The focus of AGI research is to integrate expertise in Neuroscience with expertise in Neuropsychology and Neuroinformatics. With these disciplines combined, problem-solving will be applicable to a much wider spectrum than presently available with Narrow-AI.

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