AI is arguably the hottest properties in the technology industry today. However, few people know what it is all about.
Many questions have been asked on Artificial Intelligence (AI) and machine learning by organizations all over the world. Most have heard about AI but wonder what it is and how it applies to their businesses; what are other businesses doing with AI and what they should be doing with AI. What most people and businesses don’t realize is that they have in one way or another interacted with this technology. They just don’t know it yet.
Simply put, AI can be described as the science of training machines to perform human tasks. It makes it possible for machines to learn from experience, adjust to new inputs. It is the broad science of mimicking human abilities.
Speaking during the Analytics Experience 2018 held in Milan, Italy SAS Chief Technology Officer Oliver Schabenberger said, “The point of analysis is to see something that we have not seen before. You need to find a signal in the noise and separate the signal from the noise. That really is what statistical modelling is about; that is what is AI. It is finding the signals, the patterns, the repeatable trends and separating that from the noise. It is removing the uncertainty that is in the system and getting to the story behind the huge amounts of data given.”
According to Mr Schabenberger, SAS which globally holds 30.8 per cent of the advanced and predictive analytics market share and therefore the market leader in this field- and for them the future is AI. They believe that AI is redefining innovation and turning data into intelligence enabling businesses and organizations to understand data, predict, and therefore forecast the future needs of customers by improving on existing products leading them to innovate further and make powerful business decisions. It allows for a business to predict a customer’s journey and change run the business around it.
As organizations begin to realize that AI is already and will in the near future be very crucial in decision making and innovating, MrSchabenberger says that AI will take two approaches, that is Narrow Artificial Intelligence (NAI) and Artificial General Intelligence (AGI). NAI is a form of AI that solves very specific tasks using purpose-built systems while AGI is the creation of general thinking machines with the capacity and aptitude of human intelligence is another approach Its aspiration is to realise in hardware and software human-level intelligence. AGI can solve general problems and any task.
“In AI, we are basically talking about automation and algorithmic decision making. We are talking about replacing decisions made by humans with those that are made by algorithms,” explains Schabenberger.
Moreover, he adds that it is very important that for a business to truly experience the value and growth from AI, it is crucially important that data science and business teams work together in an organization.
“The number one barrier in initializing this kind of technology in an organization is operationalizing it. There’s often a disconnect between data science teams and the business teams in organizations. When the data scientists do their work but how does the business get informed? When the business team expresses a problem how does the data science team translate it? The closer you get those two departments to collaborate the better off an organization will be,” says Mr Schabenberger.
However, AI technology has sparked huge debates globally with regards to taking over human jobs, ethics and governance. Mr Schabenberger believes that some jobs will be rendered redundant in the wake of AI.
“There are jobs that will definitely be affected by AI but there are jobs cannot be automated. For example, AI diagnoses a medical condition, we provide the care,” he says. This sentiment is echoed by his counterpart Nick Lisi, Executive Vice President, SAS Global Sales.
“AI right now is a very intriguing concept and still very misunderstood. Will some roles and jobs be displaced? Sure. However, the vision is that it will provide the ability to make more efficient the things that require more efficiency, such as healthcare, but also put power in the hands of people to make better decisions,” explains Lisi. Schabenberger further adds that AI technology is one that is very disruptive, and it is imperative that all aspects and implications of this technology are understood.
“There are systems at the moment that can diagnose skin cancer, but they have not been deployed them there are a lot of questions that arise when the diagnosis is wrong. Do you go back to the team that deployed the algorithm? Do you go back to the university that trained the team behind the algorithm? So, it is therefore very important to look critically into all the aspects of this technology,” he concludes.