Who decides what can be done in society and business? The conventional answer in Europe is that it was the church in medieval times, the state after that, and now it is a free-for-all with business having a prominent role. All parts of the conventional answer are inaccurate, and we know that the correct answer depends on the context. So, let us consider a context with very strong dividing lines: stem cell research. Stem cells are “primitive” cells that have not yet specialized into specific types, so they can be used to cure a wide range of medical conditions provided they can be coached into becoming a type of cell that needs to be replaced or repaired. They are also controversial cells because a primary source of stem cells for research and production is fetal tissue – early-stage embryos.
Church beliefs on what embryos are for and scientists’ ambitions to cure degenerative diseases like Parkinson’s and Alzheimer’s clashed, and this conflict was examined by Joelle Evans in research published in Administrative Science Quarterly. In her study, a research laboratory encountered outside pressures against the stem cell research and reacted by having internal debates and forming a response. In so doing, the scientists took on a second role as creators and marketers of a moral stance explaining why stem cell research was valuable and how it should be done.
What she documented is an unusual role for scientists. More commonly, science is thought to be a free exploration of questions for which there is no moral judgment until the time comes to use the insights. This type of scientific handoff is very common, although it has been known to create complications in some cases – such as among the scientists who developed the atom bomb, with full knowledge of the purpose of their research.
Stem cell research is not nuclear physics and has no weapons application, but the question of what kind of raw materials can be used, and how they can be used, is fraught with moral problems. These moral problems have practical implications. For example, the USA has rich access to surplus blastocysts (pre-embryos) because in vitro fertilization (IVF) procedures create more blastocysts than can be safely inserted. IVF clinics routinely destroy excess blastocysts because they are barred from turning them over for stem cell research. As of 2019, a few hundred stem cell lines had been approved for use, and these are called stem cell lines because each originates in a single blastocyst with cells that keep being reproduced.
The researchers in this study faced two debates. Externally, they faced criticism for their use of stem cells and calls to account for it morally. Internally, they differed in their views on what could and should be allowed, with the internal lines of contention being shaped by the external pressures. The need to make an external account for their work was unfamiliar for researchers and made complicated by their internal divisions.
How did they respond? Interestingly, the combination of external pressure and internal fissures helped the lead researchers formulate a set of moral values that they could justify through connecting with accepted forms of ethical reasoning and explain externally and internally.
This served two purposes. Externally, the scientists gained a role in defining the value of their work and the constraints on how it should be conducted. Internally, they unified an organization that could easily have become divided, maintaining motivation for the team members troubled by the apparent conflict of moral values. They achieved strength through unity while embracing the diversity of beliefs within their laboratory walls.
Evans J. 2011. How Professionals Construct Moral Authority: Expanding Boundaries of Expert Authority in Stem Cell Science. Administrative Science Quarterly Forthcoming.
Wait, what does it mean to be governed by algorithms? If you do not know that yet, you are not working for any of the gig contracting platforms (Uber, TaskRabbit) or employers using algorithms to assess employees and predict and manage training and promotion. The increase in data processing capacity and machine learning tools means that algorithms have crept into a multitude of organizations and influenced how they manage people. Importantly, in some places the use of algorithms is acknowledged, and the results are shared with the employees, but in other places it is secret. Some workplaces make the algorithm transparent to employees, and others make it opaque. Because people usually learn how to game transparent algorithms to get high scores, opaque algorithms are becoming increasingly common and are currently the most important to understand.
So, what do opaque algorithms do to people? That is the topic of research by Hatim A.Rahman published in Administrative Science Quarterly. He focused on a labor platform that matches freelance workers with clients. The platform implemented an opaque evaluation routine that produced a new type of quality score for freelancers that was visible to them and to potential clients. How do people react to such scores? We know that scores become goals, and people commonly try to improve their performance by making changes. That is exactly why transparent algorithms result in inflated scores after a period of adapting to the algorithm. But opaque algorithms do not tell people how to improve, making the scores produced by those algorithms less useful as goals.
Instead of targeted improvements, opaque algorithms can produce experiments to find out what elements of the algorithm affect the score, and how. Many freelancers tried to change how they worked with clients through simple actions such as changing the type of work, length of contract, procedure for closing the contract, and so on. But these changes were unlike the changes made when decision-makers face goals that are more easily understood. As has been documented in research on performance feedback, it is very common for people facing low performance relative to a goal to react by making changes to improve the performance. That happened with the opaque algorithm too, but it was much more selective.
First difference: Not everyone tried to make changes. Many individuals who were not highly dependent on the platform responded by quitting it. And this was true whether they had high or low performance, so even many high-performing freelancers (according to the algorithm) simply left.
Second difference: Not everyone’s likelihood of making changes was a result of the algorithm score. Low-performing individuals were experimenting with different approaches regardless of whether they had setbacks in their scores or not. That was important because in the platform, a score below 90% was considered low, so the result was continuing turmoil in how freelancers were working.
Third difference: Among those who performed best and were dependent on the platform, those who experienced setbacks made changes to how they worked. So far so good, especially if those changes actually improved how they worked. But what about those who did not experience setbacks in the score? They tried to limit their exposure, including by not working with new clients on the platform. Having a high score was valuable, and accepting new work on the platform might endanger it, so they preferred to stick with existing clients or to find new clients that would let them work outside the platform.
Clearly, the opaque algorithm produced scores that made it easier for clients to distinguish between freelancers, and it also governed the freelancers by changing how they behaved. Were these changes improvements? Normally performance feedback on a meaningful goal results in improvements, but it is far from clear that an opaque goal has the same effect. Indeed, the three differences in how these freelancers reacted suggest that the opaque algorithm was a poor governance tool.
Rahman, Hatim A. 2021. "The Invisible Cage: Workers’ Reactivity to Opaque Algorithmic Evaluations." Administrative Science Quarterly, Forthcoming.
The CEO of a firm is given power to control the firm. That is because the purpose of the CEO role is to create a position that has centralized control, to enable consistent formulation and execution of strategy. The CEO is in turn governed by the board of directors, who also have a say on the strategy and who assess the results of the strategy execution. So far so good, but then there is the question of how much power the CEO should have, and what happens when the CEO has too much power.
Here is a classic example of too much power: The CEO can influence how the board of others assesses the CEO by choosing the reference group of other firms and CEOs that this firm is compared against. Do some CEOs really have this power? Does it benefit them? Does it harm the firm? Research by Pino G. Audia, Horacio E.Rousseau, and Sebastien Brion published in Organization Science gives the answers: Yes, yes, and yes.
The key here is that a firm can be compared either against a standard reference group such as an industry average or a reference group that is tailor-made to suit someone in the firm. Remarkably, even though the SEC guidelines strongly warn against tailor-made reference groups, 30% of the firms in the data they analyzed had them. Interviews indicated that although this choice of reference group should be done by the Chief Financial Officer (CFO), the reality was that the CEO was often deeply involved. So yes, at least in some firms CEOs had the power to change how they were assessed.
Did they benefit from this power? The simplest and arguably most meaningful measure of benefit is how much the CEO is paid. Controlling for everything else that influences pay, CEOs of firms with tailor-made reference groups were paid more when the firm performance was lower. So, clearly the point of a tailor-made reference group was to get paid more when firm performance indicated that they did not deserve it. It was an insurance policy.
Were firms harmed? The question of harm is difficult to answer, but it is easy to discover whether others tried to penalize the firm. This they did. Securities analyst coverage and rating of a firm’s stock is very important for the firm value, and securities analysts quite systematically downgraded firms to a lower rating or even stopped following them if they had tailor-made reference groups. The firm’s owners also reacted, as they saw an increase in governance resolutions filed by shareholders at the annual meetings.
The CEO use of power to shape the assessment of the firm’s performance was consequential for the CEO and the firm, and as we might expect, in opposite directions. The CEOs used their power to benefit themselves in ways that hurt their firms. This, at least, gives one answer to the question of what it means to give a CEO too much power to control the firm.
Audia PG, Rousseau HE, Brion S. 2021. CEO Power and Nonconforming Reference Group Selection. Organization Science, forthcoming.
This blog is devoted to discussions of how events in the news illustrate organizational research and can be explained by organizational theory. It is only updated when I have time to spare.