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  • What the History of Mathematics Can Teach Us about the Future of AI

    Artificial intelligence is all around us. We use artificial intelligence algorithms every day without even realizing it. Today, face recognition helps you unlock your phone; Google translator helps you to translate any language to another language.  Alexa recognizes your voice and helps you to play your music, and you have cars which can drive themselves. Have you ever wondered how Netflix almost always manages to recommend just the right show for you? Behind all of these things are powerful machine, learning algorithms, which are built upon really simple and clever ideas. Today, we are going to take a step back and will try to understand algorithms used in AI are going into the Mathematics, which in turn has thinking and reasoning behind them.

    Whenever a powerful new technology comes along, people rush to imagine the havoc it could wreak on society and they overreact. Today we see this happening with AI. Some economists have similarly sounded alarms that automation will put nearly half of all jobs within the U.S in danger by 2030. My reading of the history of technology and experience on its frontiers make me skeptical of such claims. Major shifts in technology and AI does have the potential to be that inevitably take longer than people typically imagine transforming our jobs and lives. So societies have time to use regulations, cultural pressures and economic process that shape how that transformation happens. We are making those kinds of adjustments today with social media technology.

     

    The word “computer” was for hundreds of year’s employment title, from the 1600s onward, human computers did calculations initially by pen and paper to form navigational tables, accounting ledgers. By 1960s, the workers had slide rules and mechanical calculators to help them and still they are around us. But today we have with us smart watches which can add and subtract numbers billions of times faster than any human being. So now if we assume that NASA had no need for human computers in the 21st century, then we would be wrong. The programmers, mathematicians and computational physicists working for NASA now far away the human computers employed at the agency within the 1960s. Despite a billion-fold increase in the competence of the machines, human jobs weren’t lost they multiplied. The reason why that happened tells us a lot about intelligence, both human and artificial. It turns out that human intelligence is not just one trick or technique it is many. Digital computers excel at one particular kind of math i.e. arithmetic. Adding up an extended column of numbers is sort of hard for a person, but trivial for a computer. So when spreadsheet programs like Excel came along and allowed any middle-school child to total up long sums instantly, the most boring and repetitive mathematical jobs vanished. To tackle problems like that, you would require many clever mathematicians and computational scientists who can think of ways to program computers to do those calculations as efficiently as possible. Theorists have proved that some mathematical problems are actually complicated that they will always be challenging or even impossible for computers to solve. So at least for now, people who can push forward the boundary of computationally hard problems will never fear for having lack of work.

    Meanwhile, many of the tasks that appear most elementary to us humans like running over rough terrain or interpreting visual communication are about impossible for the machines of today and the foreseeable future. Working through mathematical problems develops your critical thinking ability and increases your capacity for solving complex problems. Excellent mathematical skills open doors to careers in exciting fields such as data science and analytics, computer programming, artificial intelligence etc. As AI gets more competent, the sphere of jobs that computers can do rapidly or more precisely than people will expand. But an expanding universe of labor will remain for humans, well outside the reach of automation.

    Whatever technical innovations are there, we have a strong scientific argument to believe that the scope of jobs involving complex computational are unlikely to be replaced by any robotic automation anytime only it will depend on high-level reasoning. Therefore, we can conclude undoubtedly “Artificial Intelligence and Mathematics are the two branches of the same tree”. “Mathematics is the language with which God has written the universe.”            

                                                                                                                                Galileo Galilei

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