There’s been a lot of mystery surrounding the use and role of Artificial Intelligence (AI) in our day-to-day lives. Pria Masson demystifies the concept and answers a pressing question:
Are machines taking over?
At the end of November 2022, there was a remarkable change in the way we interact with machines. Something called ChatGPT surfaced officially. This Artificial Intelligence (AI) tool has the potential to provide answers that are factual, realistic, clear and precise – all in a conversational manner. The internet is flooded with people playing with the options available. Apparently, it can be the answer to research, to copywriting, and basically anything that requires research and interaction. When I read about it, it really did feel like “machines are taking over”. As always, this made me delve further and while it is an interesting development, “taking over” looks to be further away.
If, like me, you are new to technology, then you too may be a bit confused with the different terms like Machine Learning and AI; and, you too may be wondering how is AI being used everywhere in everything – is it the answer to all business issues?
What is Artificial Intelligence?
AI is a broad branch of computer science that focuses on building smart machines capable of performing tasks that typically require human intelligence. It enables machines to simulate, and even improve upon, the capabilities of the human mind. Of the various elements of AI, machine learning and deep learning have seen significant developments.
What is Machine Learning?
Machine Learning is the machine’s ability to keep improving its performance without human intervention needed to explain the exact method to accomplish all the tasks it’s given. What makes this so phenomenal is that the human mind is extremely complex and knows way more than it can tell. Simple tasks like explaining how we recognise faces is difficult to articulate by a person, let alone being able to transfer that knowledge to a machine.
A Quick Summary of Developments
The most significant strides have been in the areas of perception and cognition. Perception refers to technologies such as voice recognition by Siri, Alexa etc., text recognition and image recognition. Vision systems, such as those used in self-driving cars, formerly made a mistake when identifying a pedestrian as often as once in 30 frames (the cameras in these systems record about 30 frames a second); now they err less often than once in 30 million frames. Cognition systems are those that focus on problem solving such as systems to detect fraud, prevent money laundering etc.
Perhaps the key change has been the way in which we work with machine systems. From coding machines to creating responses, machines are now able to learn from past situations and be responsive and predictive. This has been mostly through supervised learning systems i.e. in which the machine is given lots of examples of the correct answer to a particular problem. For example, JPMorgan Chase introduced a system for reviewing commercial loan contracts; work that used to take loan officers 360,000 hours can now be done in a few seconds. And supervised learning systems are now being used to diagnose skin cancer.
AI and the GCC
All the GCC governments have integrated AI into their national visions and strategic planning processes. As per a report by PWC, the potential impact of AI for the Middle East is expected to be USD320 billion, of which UAE is likely to see the highest relative gains at 14 percent of GDP and Saudi Arabia the highest absolute gains of USD135.2 billion. The region is expected to see 20-34 percent annual growth in the contribution of AI per year across the region. AI and Machine Learning is driving applications across logistics, healthcare, fintech and even recruitment.
Are Machines Taking Over?
While it seems like machines can indeed do a lot of jobs, the drivers of those actions are still going to be visionary human resources. It may be likely that almost every area of our lives and work will use AI and Machine Learning. However, it’s unlikely that they will be able to take over what people can do. The difference between success and failure is likely to be how efficient a business knows how to use these tools. And yes, they are and are likely to remain tools and aids- guided by and subject to the capability of the person guiding that tool at its initial stage. Machines aren’t taking over, Chat GPT cannot replace jobs – they can’t think, they can only learn. That’s the difference.
Pria is a management consultant who has spent over 15 years of her career helping clients across a variety of industries. You can connect with her at [email protected] and follow her Instagram handle @guide_my_idea.