Guest Post by David Stephen who discusses the importance of AI Ethics

There is a recent article, AI has social consequences, but who pays the price? Tech companies’ problem with ethical debt, stating that, “negative news stories about generative AI tend not to be about these kinds of bugs. Instead, much of the concern is about AI systems amplifying harmful biases and stereotypes and students using AI deceptively. We hear about privacy concerns, people being fooled by misinformation, labor exploitation and fears about how quickly human jobs may be replaced, to name a few. These problems are not software glitches. Realizing that a technology reinforces oppression or bias is very different from learning that a button on a website doesn’t work.”

Why we need AI Ethics to consider the impact on the human mind

AI Ethics

There are real concerns about AI and it is important to find major ethical solutions across nations. However, it may not be so great to focus on those alone. The key factor in AI’s win is the human mind. It is the mind that AI drives and affects. How does the mind work that makes this possible? It could become a path towards easing the consequences of AI across situations.

What does it mean that everyone sees the same picture, but the feeling or emotion about it is different? Why is it possible that a fake image, video, audio or text, generated by AI could become convincing? What drives certain people to do fake stuff towards certain mind targets in others?

The human mind has a structure, it has components and functions. The basis of everything that is experienced is within the mind. The ultimate question is, how does the mind work? If this is made available to accompany AI products and services, it may help to increase awareness of what it might drive within individuals or a group, preventing problems, rather than reliance on damage control.

The mind is not the brain. They are neighbors within the cranium. There are structural and functional states of the brain that can be used to understand parts of how the mind works, but the brain is biological—the mind is not particularly so.

There is what an image means to the mind, which first is to know, then proceeds to where it can be felt, then evokes emotion, before reactions. This sequence makes activities obvious across brain areas, but ultimately, the components of the mind lead.

Conceptually, the mind consists mostly of quantities and properties. Quantities relaying to acquire properties, to degrees. All memory, feeling, emotion, and reactions are properties. Properties also include craving, anxiety, anger, delight, depression, sleep, thirst, lethargy, love, dislike, interest, curiosity, ego, patience and so forth. Whatever is acquired across mind locations becomes what is experienced.

Quantities and properties have their features, but they work out what it means to have an experience of things in the external world. For AI, it could be useful to accompany a description of how the mind works with many of its outputs, to ensure that if it would drive something negative, the probable way it could be doing so is known, helping—where possible—to mitigate its captivation.

There could be a necessity to have patience in some cases to confirm certain things before taking action. There may also be a necessity to read what could be driving certain efforts or agenda. The human mind is where mental health problems are, as well as mental illnesses. It is also what makes AI make any sense.

Subsuming a conceptual way the human mind works into AI, this early, could be useful to avoid the swerves of social media that drove minds individually and collectively, sometimes for good and other times not so much.

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