ADVERTISEMENTs
.png)
Can an AI App mitigate risks of AI taking over humanity?
This article proposes an AI App through which human subjects can achieve that state and how AI devices could also be trained to shun actions that negative emotions can evoke.
Stock image. / Canva
BBC recently interviewed Nobel Laureate Geoffrey Hinton in which the latter said, there is a 50 percent chance AI will take over humanity in 5 to 20 years. In a recent interview, historian Yuval Harari narrated for the audience how AI pretended to be blind and tricked a human into solving a CAPTCHA for it. CBS 60 minutes aired three TV segments: Artificial Intelligence, nuclear fusion, and quantum computing which discussed how these scientific developments could transform humanity, but warned how they could threaten its very existence. The dark side of these developments ought to be nipped in the bud.
Central to the task for humanity is to always remain in a meditative state without conscious effort. This article proposes an AI App through which human subjects can achieve that state and how AI devices could also be trained to shun actions that negative emotions can evoke. The two together should promote a more peaceful world.
Negative emotions like anger, hatred, hostility, resentment, frustration, jealousy, fear, sorrow, and the like elevate stress levels and lower our emotional excellence, and generally make the world less peaceful. In contrast, positive emotions like unconditional love, kindness, empathy, and compassion make the world more peaceful.
Emotional excellence refers to the capacity of a human subject to remain centered in the face of extenuating circumstances. Becoming endowed with positive emotions at the exclusion of negative emotions is not an intellectual exercise, the required positive changes must come from within. A month-long self-assessment should offer convincing evidence that such is the case.
Meditation has long been known to bring about positive changes from within. The proposal here explores a data-driven AI approach to automating the meditative process with no explicit action required for the subject. Artificial intelligence modeling & optimization techniques such as artificial neural networks and genetic algorithms are appropriate since the relationships between the inputs and outputs are likely to be highly nonlinear.
Emotions cannot be measured directly; they must be inferred from secondary measurements. The secondary measurements are (1) heart rate, (2) heart rate variability (stress), and (3) respiration rate. These measurements are available on many smart watches. A gas discharge visualization (GDV) device can offer three more measurements: (4) pranic energy, (5) stress as inferred from the intensity and area of the gas discharge, and (6) chakra alignments.
Next, we must find the inputs that can potentially drive these outputs.
-
Stimulating the 33 Vertebrae. We know that chanting mantras in Sanskrit with its more than 33 alphabets, can have a positive impact on the outputs mentioned. Mantras produce vibrations and the thinking is that stimulating select vertebrae would produce a similar effect as the mantras. This of course must be proved in a research project.
-
Stimulating Brain Waves. Research has shown that meditation activates certain brain waves and has a restorative effect. Recent research also suggests that stimulating certain parts of the brain can instantly relieve stress. Thus, brain stimulation appears to be a potential input (manipulative variable) for regulating the outputs.
Experiments will confirm if the suggested inputs in fact have an impact on the outputs. The relationships between inputs and outputs are likely to be highly complex and nonlinear, and therefore, Artificial intelligence is the appropriate choice for Modeling.
If the experiments achieve success, then, the next step is to solve the inverse problem. That is, given the present values of the outputs, what inputs to apply to the subject at the next control interval such that the outputs trend in a favorable direction. The inverse problem can be solved with the genetic algorithm stochastic optimization technique.
What are the Targets. The meditative state requires that the subject remains centered in the face of extenuating circumstances. For this, the heart rate, heart rate variability and respiration rate should remain stable or trend down and the pranic energy should remain stable and trend up, stress trend down and chakras become more aligned against the central vertical line.
The subjects will find that they are remaining in the meditative state longer. These concepts should pave the way for a more peaceful world while attenuating the risks of AI taking over humanity. Additional details on artificial neural networks and genetic algorithms are in Part II of this article.
Pradeep B. Deshpande is professor emeritus in and former Chairman of the Chemical Engineering Department at the University of Louisville.
Sanjeev S. Tambe is a former chief scientist and head of Chemical Engineering and Process Development Division at the National Chemical Laboratory, Pune, India.
(The views and opinions expressed in this article are those of the author and do not necessarily reflect the official policy or position of New India Abroad)
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT
E Paper
ADVERTISEMENT
.jpg)
Video
Comments
Start the conversation
Become a member of New India Abroad to start commenting.
Sign Up Now
Already have an account? Login