LinkedIn conducted an experiment with more than 20 million users over a five-year period, and a new study found that while it was aimed at improving how the platform works for its members, some It may have affected people’s lives.
In experiments conducted around the world from 2015 to 2019, Linkedin compared weak and strong contacts suggested by its “People You May Know” algorithm, its automated system for recommending new connections to users. Randomly changed the ratio. The details of the test are detailed in a study published this month in the journal Science and co-authored by researchers from LinkedIn, MIT, Stanford and Harvard Business School.
LinkedIn’s algorithm experiment may surprise millions because it didn’t notify users that the test was underway.
Tech giants like LinkedIn, the world’s largest network of experts, routinely run large-scale experiments to test different versions of app features, web designs, and algorithms with different people.A/ A long-standing practice called B-testing aims to improve the consumer experience and keep them engaged, helping businesses make money through premium membership fees and advertising. often you don’t realize you’re running
But the changes LinkedIn made show that such tweaks to a widely used algorithm can be a social engineering experiment that could change many people’s lives. Experts who study the social impact of computing have made industry transparent by conducting long-term, large-scale experiments on people that could affect their job prospects in ways they can’t see. It raised questions about sex and research oversight.
said Michael Zimmer, associate professor of computer science and director of the Center for Data, Ethics and Society at Marquette University. “These are the kind of long-term consequences that need to be considered when considering the ethics of engaging in this kind of big data research.”
A study in Science tested an influential theory in sociology called “the strength of weak ties.” This theory claims that people are more likely to get employment and other opportunities through arm’s length acquaintances than through close friends.
Researchers analyzed how changes to LinkedIn’s algorithm affected users’ job mobility. They found that relatively weak social ties on LinkedIn were twice as effective in securing employment, he said, as stronger social ties.
In a statement, Linkedin said it “consistently followed” its user agreement, privacy policy and member settings during the investigation. Our privacy policy states that LinkedIn uses members’ personal data for research purposes. The statement added that the company uses the latest “non-invasive” social science technology to answer important research questions “without conducting experiments on its members.”
Microsoft-owned LinkedIn did not directly answer questions about how the company considered the potential long-term effects of the experiment on its users’ employment and economic status. He said he did not give department users an unfair advantage.
The goal of the research is to “help people at scale,” said Karthik Rajkumar, an applied research scientist at LinkedIn and one of the study’s co-authors. “No one was put at a disadvantage in finding a job.”
Sinan Aral, lead author of the study and a professor of management and data sciences at the Massachusetts Institute of Technology, said LinkedIn’s experiment is an effort to give users equal access to employment opportunities. .
“What they’re trying to do is run an experiment with 20 million people and, as a result of the knowledge they’ve learned, develop better algorithms for everyone’s job prospects,” said Professor Aral. I was. People have social mobility and others don’t. (Professor Allal does data analysis for The New York Times and received a research fellowship grant from Microsoft in 2010.)
User experimentation by major Internet companies has a complicated history. Eight years ago, a Facebook study was published that described how the social network covertly manipulated posts that appeared in users’ news feeds to analyze the spread of negative and positive sentiment on the platform. rice field. His week-long experiment, conducted with 689,003 users, immediately sparked a backlash.
A Facebook study that included authors from the company’s researchers and a professor at Cornell University claimed that people tacitly consented to emotion manipulation experiments when they signed up for Facebook. “All users consent before creating an account on Facebook,” the study said, “constituting informed consent for this study.”
Critics disagreed, with some accusing Facebook of invading people’s privacy and exploiting people’s moods to cause emotional distress. Others argued that the project used academic co-authors to lend credibility to the company’s research practices in question.
Cornell later said that because Facebook conducted the research on its own and the professor who helped plan the study was not directly involved in the experiments on humans, there was no need for an internal ethics committee to review the project. said.
LinkedIn’s professional networking experiments differed in intent, scope, and scale. They were designed by Linkedin as part of the company’s ongoing effort to improve the relevance of its “People You Know” algorithm that suggests new connections to its members.
The algorithm analyzes data such as members’ work histories, job titles, and connections with other users. We then attempt to measure the likelihood that a LinkedIn member will send a friend invite to a proposed new connection and the likelihood that the new connection will accept the invitation.
For the experiment, LinkedIn adjusted the algorithm to randomly vary the prevalence of strong and weak ties that the system recommends. The first wave of tests, conducted in 2015, “had over 4 million subjects,” the study reports. More than 16 million people participated in the second wave of tests in 2019.
During testing, people who clicked on the “People You May Know” tool and saw the recommendations were assigned to different algorithmic paths. Some of these “therapeutic variants,” as the study called it, caused LinkedIn users to form more connections with people with weaker social ties. I started to form fewer connections.
It is unclear whether most LinkedIn members realize that they may be subject to experiments that may affect their employment opportunities.
According to LinkedIn’s Privacy Policy, LinkedIn may “use available personal data” to research “workplace trends, such as job availability and the skills required for these jobs.” Its policy against outside researchers seeking to analyze the company’s data specifically states that those researchers cannot “perform experiments or tests on our members.”
However, neither policy explicitly informs consumers that LinkedIn itself may run experiments or tests on its members.
In a statement, LinkedIn said, “Through the research section of our User Agreement, we are providing transparency to our members.”
In an editorial statement, Science said:
After the first wave of algorithm tests, researchers at LinkedIn and MIT came up with the idea of analyzing the results of these experiments to test the theory of weak-tie strength. Decades ago the theory was a cornerstone of the social sciences, but it had not been rigorously proven in large prospective trials that randomly assigned people to social ties of varying strengths.
External researchers analyzed aggregated data from LinkedIn. The study reported that people who received more referrals for moderately weak contacts generally applied for and accepted more jobs.
In fact, relatively weak contacts whose LinkedIn members shared their interconnections only 10 times were far more productive in their job search than strong contacts whose users shared their interconnections 20 or more times. It was proved that there is
After a year of connecting on LinkedIn, people who were recommended a moderately weak connection were twice as likely to land a job at the company that the acquaintance worked for, compared to other users who were recommended a strong connection. I was.
Linkedin researcher Rajkumar said:
The 20 million users who participated in the LinkedIn experiment made over 2 billion new social connections, completed over 70 million job applications, and led to 600,000 new jobs, study reports . Weak ties proved most useful for job seekers in digital fields such as artificial intelligence, while strong ties proved more useful for employment in industries less dependent on software.
LinkedIn said it has applied its findings on weak ties to several features.
Professor Allal of the Massachusetts Institute of Technology says the deeper significance of the study is that it shows the importance of powerful social networking algorithms. This not only amplifies problems such as misinformation, but is also important as a fundamental indicator of economic conditions such as employment and unemployment.
Catherine Frick, a senior researcher in computing and social responsibility at De Montfort University in Leicester, England, describes the study as something of a corporate marketing exercise.
“There is an inherent bias in this study,” Dr. Flick said. “This shows that if you want more jobs, you should use LinkedIn more.”
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