Ethical Or Unethical Algorithms? The Crucial Challenge For AI Platforms

How will the data driven economy impact how companies sell to individuals?

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How will the data driven economy impact how companies sell to individuals?


Ethical Or Unethical Algorithms? The Crucial Challenge For AI Platforms

How will the data driven economy impact how companies sell to individuals?

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I believe that businesses are heading towards some huge ethical questions regarding AI platforms and the role of algorithms.

Marketers already have the ability to personalise marketing campaigns and even products using the data they have collected about individual customers, but as technologies develop, what happens when we can use factors such as their mood, their financial situation, their social status and more?

This ‘Temptation Island’ will cause a major ethical question over the next decade. Marketers will have to choose whether they are going to take advantage of the wealth of new technology and customer information in pursuit of profit, or whether they, as a brand, are going to adopt a more transparent or ethical standpoint.

Personalised oil pricing

One example of where we can see personalised pricing already beginning to take place is in the oil industry. One AI company is reportedly collaborating with industry giants to create a system where oil prices can fluctuate intelligently based on the financial status of the individual customer.

The company has plans to use an existing network of cameras to evaluate the customer’s brand of car, and link their license plate to their home address to give them enough data to determine how much money they have, and therefore what price they can charge them.

Consumers will then be given a personalised price via an app on their phone, which could be as much as 10% more than the next customer pays.

Some people love the idea of profit-driven, personalised pricing. However, most are very uncomfortable with the idea of a world where they can be charged fluctuating prices after being evaluated by an AI.

This is a good example of where marketers will have to make their mind up about whether they will use algorithms to drive profits against consumer knowledge. They can easily bump the prices up by 10%, and most of the time no one will ever know. It’s very likely that as soon as one company decides to do this, more will follow.

Hopper – personalised pricing for the consumer

Hopper is one of the most popular travel apps in North America. It also uses personalised pricing in a similar way to the oil industry, but the key differences are that it uses it in favour of the consumer, and it does it quite transparently.

Hopper knows when the best time to make a purchase is. They have been studying the price fluctuations of airline tickets for 10 years. If you are buying a ticket at the wrong time, the app will notify you and let you know when the best possible time to buy one is. Using the app, the average customers will get a 10-15% discount.

The app has been hugely popular – no one knows why the airline prices fluctuate but most people feel it is unfair. Hopper is a perfect example of companies using personalised pricing and algorithms – but this time to benefit consumers.

The demand for algorithm transparency

So far, algorithms have been a ‘black box’. Decisions are made for us, but we are unaware of the processes – but I believe it won’t be long until people begin asking for this to change.

Governments and industry bodies will begin to demand algorithm transparency so they can check that businesses are choosing the ethical route and ensure that consumers have fair treatment. This shift away from the ‘black box’ of algorithms will become one of the biggest issues faced by the world of AI platforms.

How will brands manage in a world of AI?

We can expect AI platforms to completely change branding and marketing. Very soon, every consumer will have an always available, omnipresent AI platform to assist them with day-to-day activities – including education, mobility, and healthcare.

AI will be able to track the usage of everyday items in the home (food, drinks, cleaning products, etc.) and will be able to outsource their purchases to an algorithm.

This could lead to a kind of subscription service, where daily products automatically come to your house when you’ve run out – the same way electricity and the internet do today. This will be a brilliant service for many, but will also revolutionise branding and marketing.

In a world of AI platforms and automated commerce, we can expect brands to fall into one of three categories:

1.       Brands that are specifically requested

These brands are loved and relied upon by their customers. Consumers will ask the AI for it every time – for example, you might ask for Colgate each time you run out of toothpaste. This is the category most brands should aspire to be in.

2.       Filtered-IN

Filtered-IN brands create good quality products that get great reviews. These brands haven’t specifically been requested by the user, but the machine recommends them based on reviews for similar users, so they get through the AI filter to reach the consumer. This is the second-best category that brands can hope to fall into.

3.       Filtered-OUT

Unfortunately, many brands will be filtered-OUT because they don’t add value to the life of a consumer – either because the price is too high, or the quality is not good enough.

In a world where algorithms choose what we see, the only way to get through this filter is to deliver a high standard product or to have a strong brand identity where consumers specifically ask for you.

There is currently have a window of opportunity for brands to ensure they are placed in one of the first two categories, but if they fail to do so, there is a good chance they could be filtered-OUT in the next phase of AI.

Prof. Steven Van Belleghem is an expert in customer focus in the digital world. He’s is an award-winning author, and his new book Customers The Day After Tomorrow is out now. Follow him on Twitter @StevenVBe, subscribe to his videos at or visit

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Ethical Or Unethical Algorithms? The Crucial Challenge For AI Platforms

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