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even, the economist? Or maybe a lawyer? Or perhaps the family/patient agreeing to use it? Again, looking
at the successes and progress (including failures) of the development of autonomous vehicles, we see that
the solution will not be easy. It will probably be different for different treatments and activities, depending
on the patient’s balance of risk and chance. Just as we agree, as road users, that the fire brigade should not
follow common traffic rules (as a delaying factor) in order to rescue people. But before we worry about
how to solve this problem for interventional medicine, we need to solve this problem for better-developed
artificial intelligence applications in diagnostics. Already today, there are companies, for example, which
diagnose on the basis of an image analysis of the cornea of the eye and bravely take full responsibility for
the opinions issued. Of course, none of these areas of diagnostic imaging (using humans or robots) is 100%
correct.

CONCLUSION
There is one more important reason why we have to rely on artificial intelligence: human intelligence
is decreasing. Humanity has reached a point where successive generations are becoming less and less
[25]
intelligent. After analyzing over 730 thousand intelligence tests, Norwegian scientists found that, the
average IQ in society is now statistically decreasing by 7 points for each generation since the 20th century.

I explain it this way. Increasingly, we are using memory and calculating and decision-making abilities in
an easier world full of computers, search engines (Google), smartphones and smartwatches. Convenience
comes at the expense of efficiency.

Since human intelligence is diminishing and sooner or later, artificial intelligence will be growing more,
many scientists estimate that in twenty years, robots will have human level intelligence. Whether the
performance efficiency then will be similar to that of the best surgeons is difficult to say but in general,
mechanics does not develop as quickly as electronics. The art of robotics is based on an intelligent
combination of mechanical work and information management obtained by sensors.

For now, information about the progress of AI in medicine is not as optimistic as we had expected.
[26]
Afterall , Medical AI, which pulled in $1.6 billion in venture capital funding in the third quarter alone,
is “nearly at the peak of inflated expectations”. Even Topol, the author of “Deep Medicine: How Artificial
Intelligence Can Make Healthcare Human Again”, also acknowledges that many AI products are “little more
than hot air”.

[27]
As the summarized IBM Watson state of art now says , “They’ve been trying to go into all sorts of things
with mixed success and one of the most hopeful things was that they would be able to revolutionize
medical care, health care. And it’s not worked because they could look up symptoms of various diseases
and they could look up cures for various diseases and they could look up medical articles. But they don’t
understand which are more meaningful than others, which medical articles are reasonable and which are
bull and so a lot of doctors have become disillusioned with Watson. And a lot of hospitals have literally
pulled the plug”.

[28]
However, there are fields of medicine, e.g., dermatology and radiology, in which we are already
successfully using expert programs. “The test, sold as IDx-DR, screens patients for diabetic retinopathy, a
leading cause of blindness, and refers high-risk patients to eye specialists, who make a definitive diagnosis.
IDx-DR is the first ‘autonomous’ AI product - one that can make a screening decision without a doctor. The
[26]
company is now installing it in primary care clinics and grocery stores” .
So why are the successes of artificial intelligence much better in image recognition? Why did deep learning
methods and currently available computing power make AI practical and useful in medicine, now? The