ARTIFICIAL INTELLIGENCE    

Artificial intelligence (AI) makes it possible for machines to learn from experience based on what it was programmed what to do.   It adjusts to new inputs and performs human-like tasks. Most AI examples that you hear about today from chess-playing computers to self-driving cars and opeating machines, small and large and it  relies heavily on deep learning and natural language processing. Using these technologies, computers can be trained to accomplish specific tasks by processing large amounts of data and recognizing patterns in the data.       

AI research in the 1950s explored topics like problem solving and symbolic methods. In the 1960s, the US Department of Defense took an interest in this type of work and began programing  computers to mimic basic human reasoning. For example, the Defense Advanced Research Projects Agency (DARPA) completed street mapping projects in the 1970s. And DARPA produced intelligent personal assistants in 2003, long before Siri, Alexa or Cortana became  household names

                                 

This early work paved the way for the automation and formal reasoning that we see in computers today, including decision support systems and smart search systems that can be designed to complement and augment human abilities.

While Hollywood movies and science fiction novels depict AI as human-like robots that take over the world, the current evolution of AI technologies isn’t that scary – or quite that smart. Instead, AI has evolved to provide many specific benefits in every industry.

AI is different from hardware-driven, robotic automation. Instead of automating manual tasks, AI performs frequent, high-volume, computerized tasks reliably and without fatigue. For this type of automation, human inquiry is still essential to set up the system and ask the right questions that will provide the answers searched for.

Making IA more intelligent is not unlike students going to school You need lots of data to train deep learning models because they learn directly from the data. The more data you can feed them, the more accurate they become.

For example, our interactions with, Google Search and Google Photos are all based on deep learning and they keep getting more accurate the more people put information in them.

Data is all around us. The Internet and its sensors have the ability to harness large volumes of data, while artificial intelligence (AI) can learn patterns in the data to automate tasks for a variety of industrial and business benefits. Some we can use at home.

The Vivint Outdoor Camera Pro can sense when someone is on your property. It will then play a whistle sound and snap a picture when the intruder looks at the camera.

There is a washing machine that knows how much detergent you need. With a fill capacity for up to 40 loads, the Whirlpool Smart Front Load Washer automatically senses load size. Called Load & Go, it’s curiously omniscient. There’s also a matching dryer.

There is a Google-powered clock that knows how to wake you up gradually. Connected to the lights in your home, the alarm clock can slowly increase the volume and lights as you wake up over a 30-minute period. The Google Assistant can even read the current news to you.

Real-world artificial intelligence has appeared culturally familiar, even cliché, long before it became real, as in the antique horrors of Doctor Frankenstein animating his monster, or the stilted behaviour of Star Trek’s Lieutenant Commander Data, or the fairy tale of Mister Gepetto making his marionette Pinnochio into  a real boy.

However nowadays, science is catching up to fiction, and unforeseen moral problems might actually arise in the future   for which the familiar storylines about soulless cyborgs offer limited guidance. Artificial intelligences are no longer simply devices programmed for certain tasks. They are learning machines, able to teach themselves based on experience, and to act upon their newly formed knowledge. As such, they threaten to escape the control of their creators.  

Artificial Intelligence is more than self-driving cars and personal assistant robots that control our appliances and order our groceries. Its intuition can be deeper and more perceptive than the suggested replies in Gmail. Its applications are increasingly diverse and invisible, from banking, health care, education, aviation, agriculture and climate change to infrastructure management, cultural promotion, and bringing to us every kind of entertainment.

Artificial Intelligence will eventually touch or transform every sector and industry.  The government of Canada said in a news release in mid-May,2019  when  it named 15 experts to a new advisory council on artificial intelligence that will  focus on ethical concerns. Their goal will be to “increase trust and accountability in AI while protecting our democratic values, processes and institutions and to ensure this, Canada has a “human-centric approach to AI, grounded in human rights, transparency and openness.

That could certainly apply in the future if police officers become robots as often described in futuristic movies. Don’t laugh. That could happen. They laughed when people were told that they someday in the future would be flying  in the air in planes. Some people laughed at me in the 1950s when I told them that someday, we will  buy things with bank cards. My teacher in grade five  laughed at me when I suggested in my essay that the day would come when planes will get in the air by simply rising directly upwards  instead of using runways. Such planes actually exist.  

It is a curious project, helping computers to be more accountable and trustworthy. But here we are. Artificial intelligence has disrupted the basic moral question of how to assign responsibility after decisions are made, according to David Gunkel, a philosopher of robotics and ethics at Northern Illinois University. He calls this the “responsibility gap” of artificial intelligence.

Google’s AlphaGo, a computer program that has beaten the world’s best players at the famously complex board game Go. Go has too many possible moves for a computer to calculate and evaluate them all, so the program uses a strategy of “deep learning” to reinforce promising moves, thereby approximating human intuition. So when it won against the world’s top players, such as top-ranked Ke Jie in 2017, there was confusion about who deserved the credit. Even the programmers could not account for the victory. They had not taught AlphaGo to play Go. They had taught it to learn Go, which it did all by itself.

That is scary. Think about this next scenario. A robotic police officer that is operated under artificial intelligence control mistakes a suspect’s move when he reaches into his back pocket to bring out his wallet and the robot shoots the man because it believed that the man was going to pull out a gun from his pocket.

A human being has brains that think and yet, a police officer actually shot a deaf man when he reached into his back pocket to being out a card that said that he was deaf.

Corporations that stand to benefit most from artificial intelligence have taken keen notice of possible failures. Driven by unease over public-relations disasters like Facebook’s alliance with political research firm Cambridge Analytica, or the death of a pedestrian in Arizona in 2018 who was hit by an self-driving Uber vehicle, they have made steps to get ahead of the problem of AI’s ethical failures.

But in some cases, the effort had failed before it even began. In March 2019, the US  Department of Defense, Google launched an Advanced Technology External Advisory Council of eight experts to guide the “responsible development and use” of AI in its products. A few days later, in April, that board disbanded amid controversy over its members, one of whom is “vocally anti-trans, anti-LGBTQ, and anti-immigrant,” according to a successful petition, and another of whom runs a drone company.

Something else is likely to take its place, of course. The problems and risks are not going anywhere, and Canada’s is not the only government studying the issue. In March 2019, , the European Union released a report, Ethics Guidelines for Trustworthy AI, that listed seven factors, with emphasis on human oversight and accountability. In this environment, ethical AI has become a buzzword, referring both to ethical applications of AI that remain under human control, but also AI that aims to be ethical in its own behaviour, free of human guidance. This latter goal is where it gets especially tricky.

How do you teach a machine right from wrong, not just in a particular case, but in general? Can a machine learn a virtue just as well as it learns a board game, or how to fly a plane?

A human can learn how to be honest and considerate but how do you program a artificial intelligence robot to have these virtues? 

If an artificial Intelligence robot can adjust its feeling on its own, what is going to prevent it into being a murderous robot that has no scruples?   That is really scary.

I have a gadget on my desk that gives me the current weather or any other info I seek but that information is programmed into the gadget. But suppose it calculates the weather on its own and when I ask the gadget what the weather is, instead of it telling me that particular information I seek, it says  “Drop dead, Batchelor!”

The possibility of anything that is programmed to reprogram itself is really SCARY.