As we stand in 2022, the terms artificial intelligence (AI) and digital transformation (DX) are linked. Even when organizations or thought leaders only name one, they will likely still be referring to both working in tandem. AI, in short, already is and will continue to power the next phase of DX initiatives and software, creating opportunities and improvements not possible previously. Since AI has myriad definitions, depending on setting and usage, we must first elaborate on its meaning as it relates to the concept of DX. Most often when AI is discussed in the context of engineering and manufacturing, we are actually referring to artificial narrow intelligence.

Artificial Narrow Intelligence (ANI), or narrow intelligence, is the courteous name for the weak AI. Narrow artificial intelligence is a type of artificial intelligence in which a learning algorithm is created to perform a single function. Any knowledge acquired through this activity will not be applied to other activities. Artificial narrow intelligence is designed to complete a single activity without human help successfully. Language translation and image recognition are two examples of common uses for narrow AI.

As we stand in 2022, the terms artificial intelligence (AI) and digital transformation (DX) are linked. Even when organizations or thought leaders only name one, they will likely still be referring to both working in tandem. AI, in short, already is and will continue to power the next phase of DX initiatives and software, creating opportunities and improvements not possible previously. Since AI has myriad definitions, depending on setting and usage, we must first elaborate on its meaning as it relates to the concept of DX. Most often when AI is discussed in the context of engineering and manufacturing, we are actually referring to artificial narrow intelligence.

The above is a hot topic, yet at the same time, for some, an excruciatingly confusing one. It isn't always a case of buzz words having precise meanings, and sometimes they may have an element of smudging in them – perhaps due to the overlap of the terms at play. Now, such is the case when it comes to Artificial Intelligence (AI), Machine Learning (ML), and of course, the seemingly newer one, Deep Learning, which ironically enough is not known as DL mostly, unlike its counterparts. Maybe, just maybe, it is too deep for it. People think AI, ML, and Deep Learning are separate entities, and they may be justified in feeling that way.

When John McCarthy and Marvin Minsky founded Artificial Intelligence in 1956, they were amazed how a machine could perform incredibly difficult puzzles quicker than humans. However, it turns out that teaching Artificial Intelligence to win a chess match is actually quite easy. What would present challenges would be teaching a machine what emotions are and how to replicate them. "We have now accepted after 60 years of AI that the things we originally thought were easy, are actually very hard and what we thought was hard, like playing chess, is very easy" Social and emotional intelligence come almost automatically to humans; we react on instinct. Whilst some of us are more perceptive than others, we can easily interpret the emotions and feelings of those around us.

Using AI successfully in the enterprise will increasingly require close collaboration between data scientists and tech-savvy business experts. Few advanced technologies conjure as much fear, uncertainty, and doubt as AI, which is alternately described by some as a destroyer of jobs and humanity's salvation. "Whereas most tech innovations have focused on solving a very defined problem, AI is continually learning and evolving even after we put it out into the field," said Beena Ammanath, a managing director and leader of the AI practice with Deloitte Consulting LLP. "Ethics comes to the forefront, as do transparency, accountability, and planning ahead for challenges that might arise if it is misused or goes rogue." According to Deloitte's latest "State of AI in the Enterprise" survey, respondents are increasingly spending on AI technologies and seeing positive returns; about half expect to increase their AI investments by 10% or more in the next fiscal year.

'It's not opening the gates of hell, but it's not a paradise,' Kasparov says about AI. Artificial intelligence learns from us, so we should really fear bad actors, not killer robots. Garry Kasparov was one of the first victims of the AI automation revolution. His loss to IBM's Deep Blue made him the first human chess champion to lose a match to a computer. But Kasparov is not jaded; his book, Deep Thinking, explores how AI can actually help us become more human. The real challenge, Kasparov told me at SXSW in Austin earlier this month, is keeping these tools from the humans who want to use them to do harm. And in that regard, we may already be too late. Dan Costa: After a career playing chess and battling Deep Blue, you've since then become a chess AI expert of sorts.

The pace of progress in artificial intelligence is astonishingly fast and it is growing at a rampant pace. Tech firms such as DeepMind, etc as well as countless academic teams at leading technical universities all over the world, have been working for years on the creation of an AI with a neural network capable of all the mental functions humans posses. Unless one has direct exposure to groups like Deepmind, you have no idea how fast AI is growing. However, it is fascinating to see how AI is transforming lives right now in its early stages of narrow intelligence: from disease detection to artificial organs, autonomous driving to manufacturing. Evolution -- the process by which different kinds of living organism are believed to have developed from earlier forms and evolution has created intelligence -- the humans, but we are the most "exceptional" form of life in existence.

Expect an enhanced workforce dedicated to AI safety, big steps in reaching what's known as "general" intelligence, and more of the same (i.e. Unlike other emerging technologies, AI never seems to go away. It's perpetually talked about, studied, revered, and feared. It's going to give robots sentience! And they're going to take over the human race!

Like paper, print, steel and the wheel, computer-generated artificial intelligence is a revolutionary technology that can bend how we work, play and love. It is already doing so in ways we can and cannot perceive. As Facebook, Apple and Google pour billions into A.I. development, there is a fledgling branch of academic ethical study--influenced by Catholic social teaching and encompassing thinkers like the Jesuit scientist Pierre Teilhard de Chardin--that aims to study its moral consequences, contain the harm it might do and push tech firms to integrate social goods like privacy and fairness into their business plans. "There are a lot of people suddenly interested in A.I. ethics because they realize they're playing with fire," says Brian Green, an A.I. ethicist at Santa Clara University. "And this is the biggest thing since fire." "There are a lot of people suddenly interested in A.I. ethics because they realize they're playing with fire. And this is the biggest thing since fire."