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Stop the Killer Robots Before They Exist


Many emerging technologies present ethical, legal, social and political challenges. We refer to the recent advances in artificialintelligence (AI), genomic research, nanotechnology, robotics, computer science and applied neuroscience.

Together, these technologies can manipulate the atoms of physical matter, digital and biological information (DNA) and nerve cells. This "nano-info-bio" convergence and its application in a military context can transform the way in which human beings go to war.


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One of the greatest ethical concerns is the dual use of scientific research for military purposes. Many scientists feel guilty for having received funding from the army to carry out their experiments. Many others refused to collaborate:
  • John Napier (1550-1617), Scottish mathematician and founder of the theory of logarithms, outlined the design of a new form of artillery that he later concealed.
  • Norbert Wiener (1894-1964), father of cybernetics who worked during the Second World War in the control and guidance of missiles, renounced his participation. He promised not to publish anything else on the subject.
  • Currently, Google withdrew from a bid for a multi-million dollar contract with the US Department of Defense to create cloud computing.

However, the potential benefit of developing technologies for civil and commercial, but also military uses, does not escape the attention of scientists and companies. Mainly because in the environment of scarce financial resources you cannot close the door to the military fund. The alternative is to leave the research career.

Machines that help judges and doctors


AI aims to create intelligent machines, but also to better understand biological intelligence. The researchers did not take long to realize that, instead of creating computers to train with large amounts of information, it was better to give them the ability to learn without an explicit program.
This is how "machine learning" and a technique within this subfield called "deep learning" were born, in which "neural networks" are developed. In other words, computational nodes interconnected with each other that mimic the ability of the human brain to perceive process and transmit information.
Machine learning has improved thanks to the large amount of information (big data) that we currently have, thanks mainly to the internet.

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AI can offer reliable diagnostics in medicine based on patient symptoms and make decisions accordingly, detect abnormalities in images with greater reliability than radiologists or promote precision medicine.
In law, AI can process thousands of sentences in a matter of milliseconds and find specific patterns thanks to sophisticated natural language (written) processing algorithms much better than lawyers or human judges.
The AI applied to transport and mobility offers autonomous vehicles or cars without driver that improve the safety and comfort of users by reducing the accident rate.

A dystopian future


Recent progress in AI, machine learning and computational vision also has, if we are not cautious, negative consequences.
  • Robots kamikazes.
  • Fleets of autonomous vehicles with the intentional purpose of colliding.
  • Commercial drones converted into missiles.
  • Videos and images manufactured to support hoaxes.
These and many other dystopian scenarios are already possible: citizens, organizations and states must face the dangers of the misuse of AI.