Best read: are algorithms taking over our shopping decisions?

Grown-up women rolling around on the floor like sumo wrestlers for cut-price clothing. Shoved and yanked everywhere and huge queues at the cash registers. Black Friday. The day after Thanksgiving when Americans are already getting their Christmas shopping done with major discounts. This chaos is shifting increasingly more from shops to the internet. The Monday after Thanksgiving, Cyber Monday, encourages consumers to shop online. They’re already spending much more online than in a real store.

Eveline van Zeeland, columnist at IO, has also noted this trend. In last week’s best read story she talks about the advance of robotized consumerism. More and more purchases in the future will be made without human interaction. Van Zeeland writes that she is a fan of a society where human intelligence is supported by artificial intelligence if needed. Of course, you have to keep an eye on the ethical consequences. But it’s nonetheless a pretty cool trend, as you can read in her column.

Rens van der Vorst calls himself a technophilosopher and gives lectures and workshops about the impact of technology on society. He also wrote the book ‘Appen is het nieuwe roken’ (App-ing is the new smoking). He thinks we should think twice before entrusting our wallet to an algorithm: “It’s a recurring issue that we haven’t found an answer to as yet. What are values are at the core? Yours or those of the technology companies?”

Automating purchases

Ask Alexa or another smart speaker to order pizza and that’s what happens. “Very handy, the algorithm selects one for you from all of the pizza delivery services. Whereas if you place an order on your laptop, you have a wider choice and are much freer. We are increasingly leaving that choice in the hands of tech companies. In the future, an algorithm will already know what you want and your food will be ready for you when you’re hungry. That’s no longer such a weird idea.”

Van der Vorst also sees the dilemma: “See, recurring purchases such as coffee, toilet paper and things like that can best be left to an algorithm. That would be pretty straightforward if it’s done automatically. These infrastructures are already in place. Look at home delivery, and various supermarkets are also working on that. But this does mean that you give up privacy: you let an algorithm view what you’re buying. In return, you get the benefits of convenience. The question always remains how much privacy are you willing to give up. The closer such an algorithm is to you as a person, the better the assumptions and recommendations will be. But is that something we really should want?”

It’s all about the money

According to Van Der Vorst, consumers hardly have a proper look at the revenue model whereby user data is used as a means of payment. “That mindset is wrong. The data we generate is the raw material used by the Googles of this world by which they make predictions. And the more data they have from you, the better those predictions become. They earn their money from this because these predictions go to the highest bidder. This leads to social deprivation,” he explains. Because those highest bidders are not the supermarket on the corner, but companies with deep pockets and good SEO. “This principle is strictly about making money. Those Google machines are not programmed to support, but to sell. The way things are going now, you can count on it being a case of only the big players staying in the game, the winner takes all.

Worldview in code

This is also a trend that Suzanna Zuboff has outlined in her book ‘The Age of Surveillance Capitalism‘. Zuboff states that we are slaves to the data economy and that tech companies do everything in their power to model our behavior in order to make money from it. Van Der Vorst summarized the book: “A big fat book that you can barely get through, but it does contain an incredible amount of interesting information that everyone ought to know. Whether it will be as dystopian as she writes, I dare not say. But we are increasingly handing over our choices to algorithms.”

More on Zuboff’s book here

Airbnb, Uber and Tinder are all examples of how we let ourselves be supported by algorithms, all in the name of convenience. “But you know what I really don’t like about these kinds of platforms,” says Van der Vorst. “I just don’t know what’s behind them. It’s a type of worldview in code. I am not familiar with that vision and I certainly don’t know how it works. Is it inclusive? Does it work honestly? When you try to gain insight into how this mechanism works, you don’t get to see it at as it’s considered business-sensitive information. Nobody knows exactly how it works. The discussion about comprehensible AI is absolutely justified. But sometimes I wonder if we actually want that. The less we know, the more we seem to rely on algorithms.”

Does this make us less sociable as people? “Automating chores such as shopping gives you more time to spend with your family or do something with friends. But we’re increasingly caught up in a tech worldview shaped by socially awkward white men. Talking to someone in real life is exciting, so romance and love are automated via Tinder. But on the other hand: how many social interactions do you actually have in a supermarket?”

Tomorrow is Good: The Professor and the Politician

The professor and the politician sat at the table of a lunchroom in The Hague with cups of fresh mint tea. The politician had invited the professor to talk about the transparency of algorithms. He wanted to set strict rules for the use of algorithms by the government, with emphasis on the word “strict,” he added.

The politician said, “I want a watchdog who will check all the government algorithms,” words which he clearly found unsavory. The professor noticed that the politician had a preference for the words “rules” and “watchdog”, and for the expression “with an emphasis on…”.

The usefulness of a watchdog

By the time they had finished their first cup of tea, they had found that there are roughly two types of algorithms: simple and complex. Simple algorithms, they thought, translate rules into a kind of decision tree. On a napkin the politician drew blocks and lines to represent this and as an example she cited the application for a rent allowance. She noted that there are already thousands of simple algorithms in use by the government.

The professor suggested that such algorithms could be made transparent relatively easily, but that this transparency would actually bring you back to the regulations on which the algorithm is based. Sipping his tea, he added: “So you could rightfully ask what the use of an algorithm watchdog would be in this case.”

At this point, the conversation stopped for a moment, but then they decided they agreed on this after all.

“B-uu-uu-t,” said the politician, looking ominous again, “then there are the complex algorithms. Neural networks and all that.'”

The professor looked thoughtfully out the window since that seemed like the right thing to do, then replied that neural networks are as transparent as the human brain. If you could make neural networks transparent, you wouldn’t be able to derive anything from them.

The politician nodded slowly. She knew that, too.

Training the network

You can train such a network, you can test the outcome and you can also make it work better, but transparency, or the use of an algorithm watchdog, wouldn’t add any value here either, the professor concluded.

Once again, the conversation came to a standstill.

The politician had spoken and the professor couldn’t disagree with her. “That’s precisely why I want a ban on the use of far-reaching algorithms by the government,” added the politician, “emphasis on the word ban.”

“The effect would then be counterproductive,” the professor said, “by prohibiting the use of algorithms by the government, you create undesirable American conditions in which commercial parties develop ever-smarter algorithms, become more powerful as a result, and in which the democratically elected government becomes marginalized.

The professor felt that the last part of his sentence had turned out to be softer than he would have liked. He considered repeating it, but instead asked “Why do you always use the word ‘watchdog’?”

“Because a watchdog conveys decisiveness,” the politician replied. “We want to make the public feel safe with the government, and a watchdog is a good representation of that.”

Curious bees

The professor was starting to feel miserable. The government as a strict watchdog? The image reminded him of countries like China. Or America.

“I don’t like that metaphor,” he said, “it has such an indiscriminate character. It’s powerful, but also a bit stupid and simplistic.

“Then why don’t you come up with a better analogy!” the politician challenged him cheerfully.

The professor was reminded of an article he had recently read and replied: “I think the image of a bee population would fit better.” It was a somewhat frivolous answer, but in a bee colony, curious bees are sent out to look for opportunities that are of value to the entire colony.

The politician laughed a lame laugh.

“Nice image, professor, but an algorithm bee wouldn’t work in the political arena!”

The professor suspected that the politician had a good point there.

They had one final cup of tea together and then once again went their separate ways.

bout this column:

In a weekly column, written alternately by Bert Overlack, Mary Fiers, Peter de Kock, Eveline van Zeeland, Lucien Engelen, Tessie Hartjes, Jan Wouters, Katleen Gabriels and Auke Hoekstra, Innovation Origins tries to figure out what the future will look like. These columnists, occasionally joined by guest bloggers, are all working in their own way on solutions to the problems of our time. So that tomorrow is good. Here are all the previous articles.

Improved level of comfort for babies in incubators thanks to algorithms and pressure sensors

Every year, around 15 million babies are born prematurely worldwide. Almost all of them spend some time in an incubator so that they can gain strength. Each of them is covered in electrodes and connected to a monitor via a tangle of wires. All of this in order to keep a close eye on the babies. An alarm goes off at least a few hundred times a day in these wards. In many cases this is a false alarm that doctors do not have to respond to. This causes ‘alarm fatigue’ among nursing staff, which means that they may be less responsive to an alarm that does matter.

Rohan Joshi has devised a way of avoiding false alarms in the event of lower heart rates or oxygen levels. One that is based on machine learning. In addition, the PhD student at TU/e uses this technique to enable critical alarms to be triggered 20 seconds sooner. Doctors at the Máxima Medical Centre are able to do their work more effectively because of this invention, . They don’t have to respond to non-emergency calls as much and can intervene more quickly when needed.

Joshi is one of approximately one hundred PhD candidates who are connected to the Eindhoven MedTech Innovation Center (e/MTIC). This is a collaboration between TU/e, Philips and three leading clinical hospitals in the region, Namely: the Máxima Medical Center, Kempenhaeghe and Catharina Hospital in The Netherlands. Within this consortium, researchers want to bring new healthcare innovations to patients more quickly. “We work in three different areas: pregnancy and birth, sleep disorders and cardiovascular diseases. In many cases, research is still carried out in an invasive manner. This can be quite daunting for patients. One of the things we want to do is ensure that patients are able to be monitored without the need for invasive contact,” says Carmen van Vilsteren of e/MTIC.

Another one of e/EMTIC’s projects: Multimillion euro grant brings artificial womb for premature babies one step closer

Increasing comfort levels

In addition to the algorithm, Rohan Joshi has also designed special pressure sensors. Van Vilsteren: “These are located in the mattress that the baby lies on. They measure the same things as the patches which are normally applied to the skin. This increases the level of comfort for babies considerably. Patients at Kempenhaeghe could benefit from this as well. They are also covered with sensors when they undergo sleep research. The ultimate goal is that people will be able to be monitored at home too.”

e/MTIC also researches solutions for cardiovascular diseases © TU/e

It is possible not only to treat a disorder, but also to prevent or detect diseases more quickly by monitoring people at home. That’s according to Van Vilsteren. “The hospitals we work with all have an enormous amount of patient data at their disposal. This enables us to provide support to physicians in a smart way. It can serve as a basis for making decisions concerning the treatment of a patient. But it is precisely through combining and analyzing all of this data across a variety of areas that you are also able to have something to say about the development of a disorder. This is how connections are found that would otherwise have remained undetected.”

More can be done under current privacy legislation than is often presumed, Van Vilsteren states. “It is often about interpreting what is conceivable within the boundaries of the law. You can see that because of this, companies and healthcare institutions are very cautious in their actions in order to avoid risks. As a consequence, they share less data or store less of patients’ data.”

That’s a pity in her opinion. “The technology that is needed to compare this variety of patient data is developing rapidly. Kempenhaeghe has an incredible amount of data on sleep. It could be the case that interesting insights could be gained by combining sleep data with heart failure data. However, the use of (patient) data should not be allowed arbitrarily, even if it has been rendered anonymous. Before you can analyze this data, you have to obtain prior consent from patients.”

Data portal

Researchers at e/MTIC are working on a data portal to make this kind of analysis and the necessary data exchange possible. “We make clear in advance what patient data can be used for and that this data is shared here solely within e/MTIC. At present you see that researchers sometimes take up to a year to set up a clinical study. They are no longer able to see the wood for the trees. That’s due to all the various rules and regulations that they have to comply with. We want to take that work off their hands by setting up that infrastructure and supporting them with their submissions. This will enable us to significantly speed up the innovation process without skipping any steps. Of course, we don’t want to act negligently or contravene any rules.”

Although e/MTIC has been officially in existence for just one year, the cooperation goes back much further than that. “The TU/e has been working with hospitals for about 25 years and the relationship with Philips goes back much longer,” says Van Vilsteren. These are no longer separate projects within the e/MTIC framework, but rather an approach based on a vision that has been clearly outlined by the parties involved. “We are working on a collective roadmap. The advantage is that we are working together with hospitals. This means that we know what is going on with doctors and patients. This allows you to come up with a solution based on specific needs. We then test a concept several times with patients and physicians. Then we take the next step in the form of a new algorithm or a prototype.”

e/MTIC has a strong industry partner in Philips.  Which makes sure that new techniques are less likely to remain on the shelf, Van Vilsteren adds. “When you first set up a medical start-up from a university, that road is often very long. A party like Philips knows its way around, which is a huge help. E/MTIC has a far greater impact because of this.”

On Friday 11 October e/EMTIC is organizing a symposium at the TU/e entitled ”Technology meets Value-based Health Care‘. This will be organized together with the Dutch CardioVascular Alliance. The inauguration of Lukas Dekker will also be highlighted. Dekker is a researcher at e/EMTIC in the field of cardiovascular diseases. Registration is possible via Mrs. A. van Litsenburg at

Start-up of the day: e-bot7 incorporates AI into customer service

“Please hold, you are next in line …” – who is not familiar with this irritating announcement, which – according to statistics – makes us spend almost 43 days of our lives on hold? With the help of e-bot7, lengthy customer service will in future be a thing of the past. The fledgling company plans to use adaptive AI in order to make this process more efficient. Furthermore, employees and bots will also be directly provided with relevant information so that they are able to respond to customer inquiries within the shortest possible time. The Munich-based start-up was founded in 2016 when the entrepreneurs – Fabian Beringer (CEO, Sales & Marketing), Xaver Lehmann (CEO, Strategy & Finance) and Maximilian Gerer (CTO, IT & Data Science) – also got so annoyed by customer service and realized that something had to change.

Fabian Beringer & Xaver Lehmann in an interview with Innovation Origins.

Please give our readers a brief history of the origins of e-bot7:

Fabian: After becoming so frustrated when we were kicked off a customer service hotline after waiting for more than 37 minutes, it was clear to us that this was a problem that had to be resolved. That’s exactly why the three of us entrepreneurs were tinkering with an idea that, with the help of artificial intelligence, would not only help agents to be able to work more quickly, but also automate recurring customer queries so that customers will be able to get their answers faster.

What makes your product so special compared to other products?

Xaver: We offer a hybrid Agent + AI platform whereby agents do not have to manually train the AI system, but it is trained automatically during business operations. We also call it “automated supervised real-time learning.” With our solution, we are able to improve customer service efficiency by up to 80%. Integration is simple and fast – less than two to four weeks – and flexible, i.e. it can be used on-premise or in the cloud. Furthermore, you will be able to use our Contextual Dialog Editor to set up complex processes, integrate them into the back-end systems and then fully automate them. We also have the most powerful multilingual algorithm as well as important strategic partnerships with EY, Sopra Steria, Roland Berger, McKinsey, Muuuh! and so on. In addition, the platform is capable of being seamlessly integrated into existing CRM systems.

Fabian: While most of those in the industry still choose to use third-party neural networks, we offer a simple interface for end clients which have our own AI developers and technologies that allow us to constantly update and improve our models, while offering each of our clients a comprehensive, customized solution to get the most out of their resources.

What major challenge have you had to overcome?

Xaver: Over the past year, our team has more than doubled and is set to keep on growing. A big challenge in this growth phase is building structures and maintaining the identity of e-bot7. Therefore it is crucial that we hire the right people.

Team: e-bot7 @e-bot7

Do you remember a particularly good time when it came to setting e-bot7 up?

Fabian: It’s very difficult to name the one best moment because life as an entrepreneur is always exciting. We are very happy to see that we can give our team members the opportunity to reach their full potential. At the same time, we are always thrilled with the great feedback we receive from our customers.

What are your plans for e-bot7’s future?

Xaver: We have a lot of stuff planned for our roadmap. One of our milestones for the coming years is our international expansion into Europe, USA and Asia. We want to become the leading provider of artificial intelligence for customer service. With the opening of new offices in London and Paris and an existing office in the United Arab Emirates, E-bot7 might be employing up to 100 people by next year.

Fabian: In addition, we want to expand and develop more languages with a focus on internationalization. In the future, companies will have to concentrate more on extending customer service in order to establish direct contact with customers. This trend is supported by new AI technologies such as the e-bot7 platform. Currently, it is technologically possible to automate up to 80% of text-based queries. We believe that full automation will take 100% longer. This would require an enormous amount of data, computational power and new technologies. As soon as this is possible, e-bot7 will become the first provider of this AI technology.

How important is this work to you?

Fabian: In our opinion, the ‘Life-Balance’ motto is not ‘Work-Life-Balance‘. E-bot7 is a substantial part of our life and we think about it all the time. That’s a lot of fun. Nevertheless it is important to take time for our families, friends and other stuff!

Xaver: It was clear to us from the beginning that you have to give your all and that there is always a solution. If you have enough stamina and ambition, hard work and the openness to constantly see things from different angles, you will succeed in moving a company forward. That’s really the kind of work we enjoy.

What is your final tip for other entrepreneurs?

Xaver: Have confidence in yourself and never give up. Many people will talk down the idea and say that it will never work. Do your own thing and realize your vision! There are some people who believe in you and will help you bring it forward.