But healthcare is where I see the biggest potential for society, both in medical research and in clinical practice.
Diagnosing a patient is, after all, just a pattern recognition task: a doctor considers your symptoms, lab results, MRI images, and so on, and compares them to what illnesses they have learned about and encountered in their careers so far. But medical professionals, like all humans, are affected by different behavioral biases, such as recency bias, which can lead to unfortunate cases of misdiagnosis. Further, consider the fact that, in the EU alone, 30 million people are estimated to suffer from one of more than 6,000 different rare diseases — and those are just the ones that we know about. No doctor could possibly learn about all these diseases in medical school.
So, one could imagine that computers might be able to assist doctors in diagnosing patients by comparing their health records to the different patterns of diseases in a database. Already today, there are studies showing that computers can be better than humans at spotting potential tumors in mammograms.
With machine learning, researchers are currently studying how innovative types of medical data, including, for example, the gut biome composition, relate to different illnesses, meaning that we will have more noninvasive tests that can catch diseases early, before they cause any symptoms.
Also, in a future where anonymized digital patient records of whole populations are available to scientists, they will be able to slice and dice the data in many ways to find more relevant insights for different subgroups of the population. Because they are typically limited in size, traditional clinical trials often gloss over differences between different age groups, ethnic groups, or groups of people with different comorbidities.
There is the potential for different digitally facilitated services to help us reduce congestion in cities. In the US, Uber offers a service called Uber Pool. Their algorithms find efficient routes for several passengers to share a ride, instead of each taking a separate car. That's brilliant. We need more approaches to society's problems like this!
Alexander: So, there are many developments on the horizon that will make our lives better!
Florian: Yes, but the digital transformation also comes with its problems. Any new technology can be used for both good and bad. For example, authoritarian governments can use facial recognition technology to implement Orwellian surveillance in public spaces.
Even in more democratic societies, the Cambridge Analytica scandal opened our eyes to how our personal data can be abused for political manipulation. Machine learning algorithms have been shown to pick up racist or otherwise discriminatory patterns from the training data that their makers feed them.
Cloud and Big Data technologies require big servers to run on, which use large amounts of energy. If not sourced from renewable sources, these contribute to air pollution and global warming. You might have seen the line “Consider the environment before printing this email,” but maybe we should also add a warning about the environmental effects of reading your mail online!
As an economist, I am also deeply concerned about the gig economy and the potential for it to create a precariat of unseen scale. Jobs with platforms like Uber, Deliveroo, and Amazon deliveries can be stepping stones for people who are able to use that income to invest in their future, but these same jobs can also create dependencies that expose workers to the pricing algorithms of these companies and leave them without any safety nets. This is why our politicians need to build the right social and economic fabric for these technologies to become a force for good for society as a whole.
Alexander: You already alluded to the changing world of newspapers and other media organizations. Given that you have had a number of clients from that sector, how do you see the digital transformation play out in that sector?
Florian: Newsrooms have been hit by several disruptions simultaneously, and I fear for quality journalism, which is in rapid decline, perhaps with the exception of the top-tier newsrooms. That is a real threat to our democratic societies, for which the so-called Fourth Estate is absolutely vital, with investigative journalism helping to hold our elected leaders accountable.
The first disruption was the loss of revenue from classified ads that followed the rise of dedicated websites such as eBay, Craigslist, Gumtree, and others (stage-one replacements of an analog product). Local newspapers were particularly hard hit by this.
Second, big tech and social media companies have become the de facto newsstands of our times, because they distribute individual news articles either directly, as in the case of Apple News or Google News, or by controlling what gets shared on their platforms, in the case of Twitter and Facebook (stage-two technologies). The result was that subscriptions and newsstand sales plummeted.
Even more worrying, industry insiders have told me that the tech giants can tell newspapers exactly what type of content and in what form they want to distribute, not to mention the power of the social media distribution algorithms that decide who gets to see what. In a way, then, they are becoming the de facto editors too.
Third, the only revenue stream left to news organizations was online ads. Yet again, big tech companies are driving this business model. Google Ads is deeply embedded in most news websites because they have all the information from tracking people across the web to serve the reader “relevant” ads — including ads for toasters, weeks after you just bought a new toaster (a stage-three technology).
The issue here is that the ads only get seen when people open the links they see in their news apps or social media feeds. Thus, a lot of what is published is often sensationalized, no matter how trite the story, so as to get you to click the headline.
Alexander: Do you mean clickbait?
Florian: In a way, yes. Engineers at social media companies can tell you that it is difficult to use natural language processing algorithms to filter out fabricated news stories on their platforms, because they are so similar to real news. Partly that is because many people who distribute false news actually believe them to be real. But the opposite is also happening: real news is using a lot of the same tactics to lure people to their sites. Quality journalism gets drowned out in a world of false and trivial content.
What is worse, in the US, there is a trend where we see political organizations, especially on the far right, buying up failing local newsrooms to spread their messages of hate and division. This is really troubling for our societies.
Now, I don't like the blanket news bashing that we hear in pub conversations or in press conferences of certain politicians, so I want to make it clear that there are still fantastic newsrooms out there, such as the Financial Times, the Wall Street Journal, and Die Zeit here in Germany, among others. By pivoting toward digital subscriptions and away from advertisement, they are able to withstand some of these negative influences. In Switzerland there is a great project, called Republik, which is a newsroom that is entirely reader-financed. But these examples are unfortunately becoming the exception and not the norm.
Alexander: You mentioned how some companies pick up on new opportunities and others miss out on them. How then should business models evolve to survive and thrive in an increasingly digital world?
Florian: Many companies use different types of digital technologies to automate and streamline their business processes, but I think you have to look at it not only from an optimization perspective, but also from the perspective of what new value you can deliver to your customers.
B2C businesses in particular have to think about how they can use digital technologies to play in the “experience economy,” as Joseph Pine and James Gilmore