We all know Facebook’s newsfeed that is used to follow the lives of our friends and family. The newsfeed has become an automated system that makes calculations on our behalf and decides which updates we should see and which we should never see. When Facebook first released this automated version of the newsfeed, few users understood this update. Many users thought the newsfeed showed them all their connections’ updates and wondered why friends and family had nearly stopped existing on Facebook. 

Facebook should have made it clear that its users were interacting with an automated system. It would have given users better control and understanding of their use of Facebook.

Many media companies use news robots to write simple articles about e.g., sports scores or stock quotes. In most cases, media companies draw attention to this. Jysk Fynske Medier, for example, writes: “Written by Jysk Fynske Medier’s article robot.”

The Israeli artificial intelligence company Faception claims that it can analyze people’s faces and predict whether they are terrorists, academics, or highly intelligent. It is, however, doubtful whether the company is capable of this at all. There is a very high risk that their algorithms will come into conflict with fundamental human rights regarding discrimination. The algorithm will likely categorize people with an Arab/ Middle Eastern appearance as being terrorists.

Corti is a Danish company that has developed a machine-learning algorithm that listens to emergency calls. The algorithm can recognize patterns in conversations. In this case, an ambulance will arrive more quickly. 

The algorithm from Corti has learned from old emergency calls data, which means that less common dialects are underrepresented. In the worst case, this could mean that the algorithm discriminates against these dialects and detects fewer cardiac arrests in areas where this dialect is present. Corti continuously checks the algorithms for bias, and in the case of the dialects, they have chosen to train the algorithm using data from several specific emergency calls with different dialects.

Mercedes and many other car companies have developed automatic systems that can parallel park a car without the driver having to touch the steering wheel or pedals. For many people, it is probably a great help. But it is also a feature that will mean that many people lose the ability to parallel park – an ability that can be useful for many years to come (before cars become fully self-driving). 

Should Mercedes (and others) instead have designed automated systems that help their users become experts in parallel parking? For example, by letting the drivers do it themselves, but advising and guiding underway?

Gradescope is a tool that helps teachers mark school assignments. The teacher uploads the students’ work in the program, which automatically gives a grade. Then the program provides an overview of how the students are doing. Gradescope also allows the teacher to add comments and correct how students are marked, so it’s not solely up to the automation. 

Gradescope has thereby ensured that the automation of marking assignments does not remove competencies from teachers. On the contrary, it provides them with benefits in the form of time saved from the manual marking of assignments and an automatic overview of students’ skills.

In 2018, Gladsaxe Municipality in Denmark developed an algorithm to identify families where the children were likely to be mistreated. The algorithm was based on a large amount of data and machine learning that calculated the probability of children being unhappy in their families. The project met with political opposition, however. For one, it was difficult to see how the algorithm decided that some children were more vulnerable than others. The lack of transparency caused citizens, politicians, and experts to lose confidence that the system was fair and sufficiently accurate. After a lot of tug of war, the project got shelved in 2019. 

Facebook has been heavily criticized for allowing political actors to use the platform to target political ads at carefully selected segments. Using Facebook algorithms, actors can hit select groups with perfectly designed messages that the public will never witness. To address this issue, however, Facebook has made political ads open to the public. Anyone can view all the ads from a particular political actor, see how much they spend on advertising, and roughly who they are targeting with their ads. 

The system is not aimed at ordinary people but rather at journalists who can use the system to monitor political parties and actors, typically during elections. The system is not perfect, but it’s an excellent example of implementing openness into an automated system. 

Facebook has employees whose jobs are to view content that is reported by users or by algorithms. But due to the amount of content on the platform, the algorithms can take complete control in certain situations, for example, during the covid-19 pandemic, when most of Facebook’s employees have been home. It has turned out that the algorithms have been the cause of much content on the platform has been deleted, or profiles have been reported without proper reasoning. Craig Kelley (an MP in the UK) has found that his posts have been deleted without explanation. After complaints, Facebook could not explain why they had been deleted and denied responsibility, but it turns out that this happens for about 300,000 Facebook posts a day.

Rainbird is a company that provides algorithmic decision-making systems to financial companies. Rainbird helps banks and insurance companies respond to customer inquiries and detect fraud. Rainbird differs from other algorithmic systems because it always incorporates explanatory systems so that customer service employees can understand how the algorithms arrive at a decision. It means that they can give their customers human and understandable explanations if their account has been closed or if they have been denied a loan.

IBM, Microsoft, and Mevii have developed facial recognition software that they claim can identify people with 99% accuracy. But a study by MIT Media Lab found that this accuracy was only valid for facial recognition of white men. The accuracy decreased when identifying women and black people and mostly with black women, where the accuracy was 65%. It turned out that the datasets for this software were images of parliamentarians, which may explain the difference
in precision.

When companies write job advertisements, they can, through their use of language, discriminate against people based on gender, age, and social background. One example is writing in a language aimed at young people rather than older people. Textio is a program that uses artificial intelligence to identify this type of discrimination and guides companies towards more inclusive language use. Companies can thus use Textio when recruiting to ensure more diversity among employees.

IBM’s artificial intelligence, Watson, is used to assist the examination, diagnosis, and treatment of patients. In 2018, it was discovered that Watson recommended incorrect and sometimes deadly medications to patients. This discovery resulted in Rigshospitalet in Denmark and Novo Nordisk abandoning their use of the technology.

When an app for digital coronavirus contact tracing in Denmark was in development in the spring of 2020, a broad societal and ethical debate arose about automated monitoring of people’s contact with each other. There was an important argument from the critics saying that the value of the contact tracing app did not measure up with the risk of the government gaining access to citizens’ location data. The risk of abuse was too big. The solution was to involve an expert group with an understanding of both ethics and technology, which resulted in a final solution where the risk of data misuse had been minimized by decentralizing data collection. The project could have been completely abandoned, but instead, it was decided to design a solution that minimized risks.

In 2011, the American t-shirt company, Solid Gold Bomb, developed an algorithm that could make funny slogans about the meme “Keep calm and carry on” for print on t-shirts. The system was fully automated, so the funny ones were put up for sale on Amazon without any people having checked the slogans. Solid Gold Bomb didn’t deem it necessary to observe the t-shirt slogans because the t-shirts would only be produced if people bought them. 

Unfortunately, the algorithm began putting t-shirts up for sale with messages like “Keep calm and kill her” and “Keep calm and rape a lot.” The case exploded on social media, and the company went bankrupt due to bad publicity.

The Danish company Holo works with self-driving buses, which are currently driving around Copenhagen, Aalborg and Oslo. The buses can only get up to a speed of 15 km/h and have never been in any accidents, but Holo has still chosen to place a living person in all their buses, ready to intervene if the bus fails or if any other problems occur in the bus.

In 2009, based on millions of users’ searches, Google Flu Trends managed to track down a flu epidemic in the United States two weeks faster than the U.S. Center for Disease Control and Prevention. Due to this, the expectation became that Google’s algorithm could predict precisely where and when an epidemic would strike in the future. But after 2009, Google’s predictions became inaccurate, and on several occasions, the service overestimated the scale of the outbreaks to such an extent that Google Flu Trends went extinct after five years.

When listening to music on Spotify, the company collects data about users’ taste in music used to generate music recommendation lists. It could develop into an echo chamber where the user listens to some music, gets recommended more of the same, and keeps listening to the same kind. But Spotify’s algorithms are good at testing the limits of their users’ musical taste, which means that users are constantly allowed to listen to new music and test their limits. The result is that the algorithm both helps push people’s music taste and follows when people change it over time (unless they are stuck on old eighties songs).

A Vietnamese IT security company has demonstrated that they can hack the facial recognition feature on an iPhone X. This is done by making a 3D printed “twin mask” for less than 2,000 Danish kroner (around 300 euros). So you do not have to be an expert in computers to break into an iPhone -all you need is a picture of your victim and access to a 3D printer.

Google is the world’s most important search engine, and it can be life or death for businesses whether they are at the top of Google’s search results or not. Therefore, of course, many try to figure out Google’s algorithms so that they can get higher up on the results page. Sometimes people cross the line and use methods that try to hack Google’s algorithm. It is also known as black hat search engine optimization. 

Google is in a perpetual battle against these hackers, who do not break into Google’s systems but try to hack the data that Google uses to rank results. Google has so far won the battle against the black hats. But it is an eternal battle that requires thousands of dedicated employees who are constantly developing their algorithms.