By Akinsola, JET Ph.D.
Artificial intelligence (AI) is the latest disruptive technology, and the most consequential. Here is what it is, what it is already doing, and what we should worry about.
Every era has a technology that makes the old way of doing things look quaint. Electricity did it to candlelight, and television did it to the radio evening. The automobile did it to the horse. Today the technology in question is artificial intelligence, and it is quietly moving into almost every part of working life.
A quick definition
At its core, AI means machines imitating the way humans think and behave. It borrows from philosophy, psychology and linguistics, and it rests on a handful of building blocks: learning from data, understanding human language, perceiving the environment, planning, and controlling robots.
Researchers usually sort AI into four stages. The first is the reactive machine, which responds only to what is in front of it. IBM’s Deep Blue chess computer is the classic example. The second stage is “limited memory”, systems that improve by learning from past data. Most of the AI we use today sits here, including the recommendations on your phone and the fraud alerts from your bank.
The third stage is “theory of mind”, machines that grasp human thoughts and emotions. It is still largely ahead of us, though researchers are inching toward it in driverless cars and digital assistants. The fourth is true self-awareness, which for now belongs to science fiction.
Why “disruptive”?
The word comes from Clayton Christensen, the Harvard Business School professor. A disruptive technology does more than improve on what exists. It replaces an established product or process, and the challenger usually comes from a young company rather than an industry giant.
Examples are everywhere. Netflix took on the video rental shop and cable television, Uber took on the taxi rank, and Airbnb took on the hotel. Behind all of them stands the Internet, the original disruptor, on which most later ones were built.
AI is different in kind. Most disruptors upend one industry, but AI is reshaping nearly all of them at once.
The fuel is data
AI is powerful now because of data. One widely cited estimate said that in 2018, 90 percent of the data generated each year had been created in just the previous two years. Every click, purchase and message adds to the pile. Machine learning turns that raw material into predictions, and prediction is the product that businesses increasingly pay for.
Five faces of business AI
For business, AI comes in several flavours and they are listed thus:
Interactive AI is the chatbot or virtual assistant that answers customers at any hour.
Functional AI goes beyond advising and acts. It can spot a failing machine in a factory network and shut it down, or direct warehouse robots to bring shelves to human pickers.
Analytic AI combs through large datasets to assess supplier risk or gauge customer sentiment.
Text AI converts speech to text, translates languages and finds the right document even when the keywords don’t match.
Visual AI lets an insurer assess vehicle damage from a photograph, or lets a packing house grade apples by size and colour.
Sector by sector Application of AI
In finance, algorithms judge creditworthiness from digital footprints, price insurance policies to individual behaviour and flag suspicious transactions. In marketing, they predict what a customer will want next and generate content tailored to each reader. Online retailers use the same tools for product recommendations and round-the-clock chat support.
Contact centres show both the promise and the gap. In one study of 362 firms cited in the research, 80 percent of chief executives thought their customer experience was excellent, while only 8 percent of customers agreed. That gulf is exactly where AI, which can learn what customers actually want, is being deployed.
Telecommunications operators use it too. Neural networks forecast traffic so networks can be reconfigured before congestion hits, and self-healing systems restart faulty servers without waiting for an engineer.
The business case
The benefits that companies cite are consistent. Decisions are faster, and in a competitive market speed matters. Routine data work is automated, and some estimates put the productivity gain at 40 percent or more, though such figures deserve scepticism. Fewer human slips mean better quality, and many firms report lower costs. For a small business with limited funds, that can be the difference between surviving a hard year and closing.
The other side of the ledger
Any honest account of AI has to include what it costs us, and the costs are real.
Deepfakes can put a stranger’s face and voice into fabricated video, and they threaten reputations and public trust. Facial recognition has wrongly identified innocent people as criminals, with documented cases of false arrests that fell hardest along racial lines. Behind both problems sits a larger fear about work. If machines can do a task faster and cheaper, what happens to the people who used to do it?
There is no tidy answer, and the research is candid about that. It calls instead for a serious, evidence-based response so that no part of society is left behind. That means retraining workers, being open about how algorithms reach decisions, and having regulators who understand the technology. Nigerian scholars have made the same argument, urging regulators to keep pace with disruption rather than chase it after the damage is done.
What now?
It is easy to dismiss AI as hype or to treat it as destiny, and both views are mistakes. The better view is that this is a tool, and a very powerful one that will change how business works. The Internet reshaped commerce within a generation, and AI is likely to move faster.
For business owners, the sensible step is to learn what the technology can and cannot do, and to start with a concrete problem rather than a buzzword. For governments, the task is to set sensible guardrails before the harms multiply. For the rest of us, it is to stay curious and a little sceptical.
The machines are not coming, because they are already here. What remains open is whether we shape how they are used or simply live with the consequences.
Akinsola, JET Ph.D.
akinsolajet@gmail.com
+2348171861859
'
'Do you want to share a story with us? Do you want to advertise with us? Do you need publicity for a product, service, or event? Contact us on WhatsApp +2348183319097 Email: platformtimes@gmail.com
We are committed to impactful investigative journalism for human interest and social justice. Your donation will help us tell more stories. Kindly donate any amount HERE
'