According to a new study, LinkedIn ran experiments on more than 20 million users over the course of five years that were meant to improve how the platform worked for members.

Linkedin randomly varied the proportion of weak and strong contacts suggested by its "People You May Know" system over the course of three years. A study detailing the tests was published in the journal Science.

Millions of people may be surprised that the company did not inform them that the tests were happening.

Tech giants likeLinkedIn run large-scale experiments in which they try out different versions of app features and web designs on different people. The purpose of A/B testing is to improve consumers' experiences and keep them engaged, which helps companies make money through premium memberships or advertising. Users don't know that companies are testing on them.

The changes made by LinkedIn are indicative of how social engineering can change lives. According to experts who study the societal impacts of computing, conducting long, large-scale experiments on people that could affect their job prospects, in ways that are invisible to them, raised questions about industry transparency and research oversight.

The director of the Center for Data, Ethics and Society at Marquette University said that the findings suggest that some users had better access to job opportunities. There are long-term consequences that need to be contemplated when we think of the ethics of big data research.

According to the strength of weak ties theory, people are more likely to gain employment and other opportunities through arms length acquaintances than through close friends.

Users' job mobility was analyzed by the researchers. Weak social ties onLinkedIn proved to be more effective in securing employment than strong social ties.

During the study, Linkedin said it had acted consistently with its user agreement, privacy policy and member settings. The privacy policy states that data is used for research. The statement said that the company used the latest social science techniques to answer important research questions.

A question about how the company had considered the long-term consequences of its experiments on users' employment and economic status was not answered by the company. The research didn't advantage some users.

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One of the study's co-authors is an applied research scientist at LinkedIn. Everyone was given the same chance to find a job.

The lead author of the study was a management and data science professor at M.I.T.

Professor Aral said, "rather than anointing some people to have social mobility and others, they are trying to do an experiment on 20 million people." Professor Aral received a research fellowship from Microsoft in 2010 after conducting data analysis for the New York Times.

There is a checkered history of experiments on users by internet companies. Eight years ago, a study detailing how Facebook had quietly manipulated what posts appeared in users' News Feeds in order to analyze the spread of negative and positive emotions on its platform was published. The experiment caused a backlash.

The study claimed that people had consented to the experiment when they signed up for Facebook. The study said that all users agree before they create an account on Facebook.

Critics accused Facebook of invading people's privacy while exploiting their moods and causing them emotional distress. The project used an academic co-author to lend credibility to problematic research practices, according to others.

The ethics board at Cornell didn't have to review the project because the professor who helped design the research hadn't done any experiments on humans.

ImageWhether most LinkedIn members understand that they could be subject to experiments that may affect their job opportunities is unknown.
Whether most LinkedIn members understand that they could be subject to experiments that may affect their job opportunities is unknown.Credit...Linkedin
Whether most LinkedIn members understand that they could be subject to experiments that may affect their job opportunities is unknown.

The professional networking experiments were different from each other. As part of the company's efforts to improve the relevancy of its "People You May Know" algorithm, they were designed

Data such as members employment history, job titles and ties to other users are analyzed. It tries to gauge the likelihood that a new connection will accept a friend invitation from a member of the professional networking site.

The system recommended strong and weak ties for the experiment. The first wave of tests had over four million participants. More than 16 million people took part in the second wave of tests.

People who looked at recommendations and clicked on the "People You May Know" tool were assigned a different path. LinkedIn users formed more connections to people with weak social ties due to some of the treatment variant. People formed less connections with weak ties because of other changes.

It's not known whether most LinkedIn members are aware that they could be subject to experiments that could affect their job chances.

The company may use personal data available to them to research workplace trends, such as jobs availability and skills needed for these jobs. The policy for outside researchers states that they will not be allowed to experiment or perform tests on our members.

The policy doesn't tell consumers that LinkedIn can do experiments on its members.

In a statement, the company said that they are transparent with their members.

It was Science's understanding that the experiments undertaken by LinkedIn were conducted under the guidelines of their user agreements.

The theory of the strength of weak ties was tested after the first wave of testing. Although the decades-old theory had become a cornerstone of social science, it had not been rigorously proved in a large-scale prospective trial.

Aggregate data was analyzed by the researchers. According to the study, people who received more recommendations for weak contacts applied for and accepted more jobs.

The study said that weak contacts with less than 10 mutual connections were more productive than strong contacts with more than 20 mutual connections.

Compared with other users who received more recommendations for strong-tie connections, people who received more recommendations for weak-tie connections were twice as likely to get a job at the company where they worked.

The researcher said that weak ties are the best option for helping people find new jobs.

More than two billion new social connections were created and 70 million job applications were completed by the 20 million users who were involved in the experiment. Weak-tie connections were the most useful for job seekers in digital fields, while strong ties were more useful for employment in industries that relied less on software, according to the study.

A new tool that notifies members when a first- or second- degree connection is hiring is one of the things that was applied to the findings. The company didn't make study related changes to its feature.

Professor Aral of M.I.T. said that the deeper significance of the study was that it showed the importance of social networking to the economy.

The study was described as a corporate marketing exercise by a senior researcher.

There is an inherent bias in the study. If you want to get more jobs, you should be on the professional networking site.