AI-washing: is it machine learning … or worse?

AI-washing: is it machine learning … or worse?

Dr Bimal Roy Bhanu

CEO at AiXPRT

Views 473

AI-washing: is it machine learning … or worse?

14.11.2019 12:15 pm

There are widespread misconceptions about Artificial Intelligence (AI), including its powers and what it can and can’t do. Which means that potential users may have unrealistic expectations of what they will see when they’re presented with AI. For some, it conjures up images of robots, while others expect it to be able to solve all problems and automatically understand numerous manual processes and tasks without training or configuration. The truth is that while AI has advanced exponentially over the last decade, it is still really in its infancy.

The gap between reality and marketing is exacerbated by the existence of some business technology solutions claiming to have artificial intelligence capabilities when they don’t. This is the world of ‘AI-washing’ which is becoming something of a phenomenon with some so-called AI solutions merely being data aggregators. At best they’re offering machine learning solutions, whereas at worst they’re just providing software algorithms. This has been occurring for a while: in the summer of 2017 the research and advisory company Gartner stated: “many technology vendors are now ‘AI washing’ by applying the AI label a little too indiscriminately.”

Why is it happening? Sadly, it seems mainly down to commercial opportunism. There is a belief that even falsely using the label of AI will elevate the value of the software company’s solution, no matter how dated it may be. It makes it appear to be cutting-edge innovative technology, thus warranting a higher price and generating more revenue per product sale. Vendors who haven’t kept up with innovation or who haven’t invested in true AI solutions may think that they can hide behind the plethora of misconceptions about AI by branding their products as being AI powered solutions. This means that companies may be purporting to use AI but are in fact using Robotic Process Automation or Big Data analytics.

Buyer beware, what’s on the tin may not be what’s inside it. If in doubt whether you’re evaluating a genuine AI solution, here are some questions to ask the software vendor:

·         Can your solution be continually taught or trained on multiple use cases by a business user without any AI knowledge or data analytical skills?

·         Does the AI software continue to learn from what it is being taught?

In both cases the answer you’re looking for is yes.

You could also ask the vendor:

·         How do you define AI?

·         What AI technology does your solution use?

Big Data and the growth of the Internet of Things have created a fertile breeding ground for AI application solutions across multiple sectors from financial services to health and education. It is critical to the development of company strategies to understand the impact of AI on a business, as it affects their market(s), their customers’ needs and the changing nature of business competition. Used correctly, AI adds real value by transforming a business process or issue.

There’s no doubt that genuine AI solutions have revolutionised technological capabilities with their ability to artificially create instantaneous and automated high functioning human-like intelligence. They deliver automation to business processes, pull unstructured data from documents, drive efficiencies by saving time and costs, reduce risks, provide advanced real-time analytical insights to empower decision making and function like a human brain. Genuine AI is intuitive, powerful and accurate.

In terms of regulatory compliance in financial services - for example automating the KYC processes for AML and CTF - the utopia is an AI solution system that harnesses machine learning and natural language algorithms. The AI engine should not be static, but it should be trainable to understand any regulation regardless of geography. Also, once the system has learned a regulation, it should be simple – using a straightforward text input interface – to teach the engine to understand any differences or changes in regulation. It might take a person weeks to understand and be trained for changing regulations, whereas the AI solution can do it in a matter of hours.

Given that it can take months to manually complete compliance assurance processes, the business case for embracing the automated efficiencies, cost savings and analytics delivered by AI compliance solutions is undeniable. Such platforms are available and are infinitely superior to the illusory masquerade of the AI-washing brigade.

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