Sherlock or Moriarty – how do you approach AI?

Publish date:

Understanding the different personalities of AI.

From Skynet to The culture, science fiction is littered with utopian and dystopian views on what AI will bring. But there is a more fundamental question when it comes to AI, is it there to solve problems or exploit information? Sir Arthur Conan Doyle created two competing personalities that characterize this challenge. Sherlock – the problem solver, the analytical mind (accompanied by an often-startling lack of social skills), and Moriarty the criminal genius who exploited information to get power.

These two distinct personalities sum up two different mentalities when we look at how to use AI, namely the use of data to solve a known problem, or the use of data to create new markets and rise above the competition. It is important when you are looking at an area of your business to understand which of these mental models are most appropriate. The theoretical answer is „both” but the reality is that they represent two different, but potentially symbiotic, approaches.

Let’s start with Moriarty and the other character for whom information is power – Mycroft Holmes. In this model, having information represents a business opportunity. Examples today would be social networks such as Facebook and Twitter, the search history from Google and the buying habits from your credit card. The data scientists are after the information because data can bring great value to the company.

In this model, AI acts as a secondary character rather than being the main protagonist. To use a modern example, the Russian Government leveraged Facebook’s extensive information set to influence the US Presidential election in 2016. Facebook is critical in this power dynamic as it is only via the information within Facebook, and other social media networks, that Russia was able to perform the analytics to target the right people.

In the world of Mycroft and Moriarty, having information represents power. It’s not simply a necessary step towards a goal but it represents the goal itself – To know more than others, and through that, be able to better target, better sell or better change the real world.

For a company, the ambition may not be as large or as broad sweeping as any social media platform, but it is important to identify those information sets that your company has, or could create, which would truly represent a powerful data asset to the firm. These data assets could be sold to others or represent power because they enable you to know what others do not know. In a tiny sense the current financial information of a firm represents a powerful data set. It is the reason why there are closed periods to prevent insider trading – distorting the market based on pre-knowledge of a company’s position.

But with big data, IoT and AI, these data sets can become much more numerous and impactful. Imagine a network product supplier who is able to understand true network quality through their own as well as their competitors’ devices. A city that is able to truly understand how its citizens live, a travel company that understands the emotions of its customers as they go through their experiences. These are the powerful information sets that can provide new opportunities and represent new boundaries for the business relative to the competition.

The other model is the Sherlock model, the information is already there, everyone has access to the same information as Sherlock. But what he is able to deduce and infer from that information is obvious to him but not visible to anyone else. Sherlock is the data scientist, the algorithm, and the machine learning that helps us see things that others have not seen, and solve problems that others have not solved. In this model having data is a given, it might be challenging to get, but the access to the information itself is not the competitive advantage.

This is where the outcome is the true goal. Outcomes such as; curing cancer, reducing customer churn, reducing stock levels or creating a conversation to increase customer loyalty. The information may already exist, but your competitive advantage will depend on the algorithms and the ‚brains’ that are working on the data.

When looking at information and AI it is important to understand which role you are going to play, Moriarty (or Mycroft) or Sherlock. The mentalities are different, the challenges are different. Sherlock is the analyst, Moriarty the AI Engineer. Moriarty’s and Mycroft’s power comes from their ability to bring things together, this requires governance, organization, control, it is about ensuring the quality of the information and making sure it is timely and is delivered to the right points to maximize impact. Sherlock’s power comes from taking that information and delivering the output. Your organization needs both, but Sherlock does not make a great AI engineer, he lacks the patience and organization, Mycroft and Moriarty meanwhile lack the focus to truly achieve the outcome.

So as you look at your AI and data challenges, remember that the full story requires multiple personalities, multiple perspectives and it is crucial to have the right personalities focused on the right thing in the right place and at the right time. Taking this thought forward we are redefining how we approach Artificial Intelligence and are working with businesses to deliver real-world solutions for sustainable and trusted business performance.

Powiązane posty

Artificial Intelligence

Why think in the past when you can dream of the future?

Jeff Bird
Date icon 2019-03-15

AI is affecting everyone’s lives, both in business and personally. The launch of Google’s AI...


Making AI human: transforming the customer experience through artificial intelligence

Yashwardhan Khemka
Date icon 2018-11-29

Many organizations are looking at the AI-driven customer experience as yet another IT...

Artificial Intelligence

RPA and AI across the intelligent automation spectrum

Jayant Ingole
Date icon 2018-11-27

RPA and its expansion into AI is helping to drive a new era of business and IT alignment.