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Combatting the Effects of Implicit Bias in Faculty Searches

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Great work by social and cognitive psychologists over the past few years has revealed one weakness of human judgment by developing the notion of “implicit bias,” often taken to mean embedded stereotypes that heavily influence our decision-making without our conscious knowledge. (Take your own implicit bias measurements). As the work evolved some are attempting various interventions to stimulate active reasoning to interrupt the unconscious judgments (see here, for example).

That research investigated some mitigations like efforts to actively recognize stereotyping in a given context; to consciously reflect on individuals who violate the stereotypic assumptions; to seek more detailed information about individuals of a given group based on personal, rather than group attributes; to take the perspective of a member of the given group; and to increase interactions with members of the given group. The experiment showed some impacts of these simple interventions.

Some of the interventions appear to succeed simply by our becoming aware that we are subject to unconscious influences on our judgment. This knowledge alone appears to act as a brake to “fast-thinking” decisions, as Kahneman calls them. It allows our values to be more explicit inputs to our evaluations of others, rather than using superficial criteria.

These are issues that all of us face in daily life, but they are of specific interest as we mount searches for new faculty in the coming year. How can we wisely achieve our goal of increasing the diversity of faculty?

Some lessons of other universities speak to the importance of diversity within search committees themselves; others focus on recruiting actively to produce a diverse pool of candidates from the inception of the search process. And then there are efforts to expose potential effects of implicit biases.

We think we can apply these research results about implicit bias to faculty search committees as part of orientation for search committee chairs. Led by our new Vice-Provost for Faculty, Reena Aggarwal, in collaboration with Rosemary Kilkenny, we also plan to have materials that other search committee members can use.

These efforts are probably most important after fully deterministic criteria are applied. That is, sometimes we receive applications for tenure line positions from Phd’s in the wrong field or from ABD candidates. Sometimes an assistant professor from a lower ranked institution applies for a chaired full professor appointment. Such applications can be easily rejected as unambiguously unqualified.

Some of the techniques are simply ways to force more attention to an evaluation – returning to the stated search criteria, forcing explicit documentation on strengths and weaknesses in addition to overall ratings.

Search committees administer complicated multidimensional and inherently subjective evaluations of potential faculty colleagues. Slowing down the thinking and understanding the individual candidate as much as possible are worthwhile goals.

Taking Care with Big Data

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I recently read a news article about a household tragedy related to sloppy use of big data. The offending event was connected with a digital portal that provided street addresses based on an IP address for an Internet connection. IP addresses cannot be mapped specifically to a street address in many cases, but can be mapped to a smallish geographical area. However, some IP addresses cannot be mapped at all. For those IPs, the mapping service chose a spot in the middle of the country, in Kansas, as the “default” position. Since the mapping problem with IP addresses is indeed prevalent, there were millions of such IP addresses that were mapped to the same default address.

One use of the service was apparently the assignment of a street address to IP addresses that were suspected to be involved with criminal activity. The outcome of the assignment practice as used by the law enforcement agencies was to investigate possible criminal activity at the house. Understandably, this came as quite a surprise to the owners, as wave after wave of different law enforcement agents descended on their house. They’re suing the data-mapping firm.

What went wrong here, from a data ethics point of view? (By “data ethics” here I mean honest communication of what is known and not known about the data.) The mapping firm has many records for which a street address is unknowable. They face a choice. They could mark the case with a code that denotes their own lack of knowledge. They would, therefore, admit that their information is incomplete for any purpose. Or, if they knew that the case lay within a specific country but not exactly where, they could have used a code that denoted that fact itself (“inside the US, not known where”). That code would thereby communicate the level of knowledge they do possess as well as the level they cannot possess.

Instead they chose to impute a specific location. Their imputation, however, was of the grossest type, probably choosing the geographical center of the country. In the best of circumstances, this will be incorrect for all cases but a very few. Perhaps the biggest irony of the story is that after the lawsuit the firm is reported to have changed the location chosen as the default location for cases missing location data. It is reported that they have chosen to impute into all those records a single location that is in the middle of a lake! (One can only imagine what law enforcement agents will do, given this information.)

All data have errors. In a colloquial sense, all data are wrong. But sometimes they’re useful for a given purpose. This occurs when the data are well described and curated in a manner to anticipate multiple uses. Further, the nature of the data is communicated to users in order to minimize uses that are not well supported by the data attributes. Finally, users have a responsibility for appropriate use of data, to know what the data describe well, and to know uses for which the data are ill suited. This requires some attention to detail.

The news story does not elaborate on what is known about the documentation provided users about the nature of the street address information, nor about the sophistication of users. But harm was done to the owners of the default address, harm that could have been so easily avoided with practices common to research data sets. The fact that the “correction” of the default address was to choose a point in a body of water demonstrates how much basic understanding of data ethics is lacking in the data owner.

Liberal Education and Life Expectancy

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One of the fastest growing populations in the US over the past years has been those who are 100 years or older. What changes they have seen during their lifetimes! In 1916, there was no television, movies had no sound, antibiotics had not been discovered, nor had fluorescent lights and even store-bought pre-sliced bread. Many workers worked much more than 40 hours a week; most births took place at home; few teenagers were in high school but instead were working; the number of horses and mules in the country was hitting its peak; few households had electric refrigerators; fewer still had radios.
Enormous changes took place during their lives, and yet, it seems, the rate of change, especially in technology, is vastly much faster now. Imagine what those passing 100 years old in 60 years — today’s forty-year olds — will have experienced in their lives!

All of this is relevant to us in academia, as we attempt to prepare 18-22 year olds for 80 years or more of life after university. It seems clear that when many of the basic features of liberal education were formed, the notion of preparing for a life of 100 years was not in scope. What does this mean for us now?

Many are speculating now about what are the essential ingredients in the design of liberal education. Is it the exposure to the enduring questions of human life? Is it coextensive with the development of deeper understanding of ourselves, as individuals – the sense of interior freedom, insight that allows us to live an authentic life, as Presdient DeGioia stated in his November 20, 2013, launch of Designing the Future(s) of Georgetown? Is it the exposure to a learned, older mentor who guides the synthesis of information in a given field? Is it the acquisition of the thirst and ability to self-teach? (Or, as President DeGioia states – “how to integrate, appropriate, challenge, and critique knowledge—how to see patterns, make connections, identify anomalies.”)

By design, liberal education gives higher odds that the students learn a variety of tools of acquiring, critiquing, and synthesizing new knowledge. They have chances at exposure of different ways to acquiring knowledge — deep reading of text, careful objective observation of events, structured measurement, the randomized experiment, and the simulation. They have chances of alternative expressions of knowledge, with creative and alternative literary forms of writing, with data visualizations, with video demonstrations, with oral presentations

As we discuss the future of liberal education, it would be helpful not to focus on the outcome of a new graduate in their early twenties, but instead, at their 80 year-old self. It is not at all unlikely that they will be engaged in the labor force, working actively to earn a living.

What will they be doing? What attributes of their character will they need to draw upon for energy and meaning? What knowledge will they require to be successful and fulfilled?

It does seem simple to speculate that longer lives lived will be best lived by those who are facile with change. Change will require learning new things. Learning new things requires cognitive tools, precisely those for which liberal education is so well suited. They have a strong chance of creating life-long learning and self-renewal that can maybe even last through age 100.

Sparking Attention by Expectancy Violations

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I have vivid memories of working on a research project, some years ago, feeling great confidence about its likely outcome. I was working late at night and there, in the results, was a completely unexpected, contrary-to-dominant-paradigm result. We made sure it was checked over and over again. We looked over each observation on which the conclusion was based. We couldn’t make it go away. It stimulated a whole set of new research, energized in a way uncommon in my career. That one unexpected finding was so riveting that it spawned years of work.

Recently, I encountered some commentary on learning among infants. There is now growing evidence that infants focus much more intensely on events that defy prior expectations. The experimental manipulations included a ball rolling down a ramp and apparently passing right through a solid wall. The 11-month old infants demonstrated quite unusual attention to this event relative to those that exhibited expected outcomes. In later experiments, the research showed that retention of learning was enhanced in conditions with the heightened attention. The unexpected occurrence triggers alertness, which in turn facilitates learning.

While this has obvious implications for education and experience-based learning, the results also have implications for navigating differences among us as humans. With every new tragedy or violent event in our society, we hear calls from leaders for more dialogue, listening, learning about one another’s point of view, walking in one another’s shoes. Our diversity becomes a strength only if we interact with one another.

One of the horrible features of stereotypes is that we end up expecting another to behave based only on a very limited set of information about them – their race, their gender, their age, their clothing, their speech. What we often learn, over and over again, is that no one person is so simply defined that one or two attributes determine their essence. We are all unusually complicated creatures. We have personal interests, which are not observable. We have individual ambitions, which can be learned only by engaging in dialogue. We have our own unique history, different from others who look like us. We have our own internal identities, which are complicated and elaborated. There is a surprise within each of us. But the surprises are revealed only through interpersonal interaction.

So what does this have to do with infant learning? Dialogue with another person almost always reveals an anomaly with a stereotype – the prediction based on looks fails miserably to capture the real essence of the person. When humans encounter the unexpected, just like the infants in the experiment, that’s when learning becomes self-motivated. When we observe characteristics that don’t fit our prior experience, we become interested and engaged.

The understanding resulting from this learning can be achieved only when we discover what’s beyond the obvious.

Academic Master Planning: Space for Education and Research

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Over the past few years, led by campus architectural consultants, faculty representatives, and facilities’ administrators, we’ve been engaged in imagining alternative futures for the Georgetown academic facilities.

The planning time horizon for the discussion is long (10-20 years). The work acknowledges that space constraints on the Hilltop campus do not permit innovation at the rate we have experienced in past decades.

Some of this work has addressed new space needs on the Hilltop campus; other work has addressed alternative expansions of our downtown locations.

In one sense, this is a logical evolution of work on the “campus plan,” which addressed key Hilltop issues of future dormitory needs, renovation/replacement of key existing buildings, and integrative approaches to space on the Medical Center and the Main Campus. Academic Master Planning is the rubric for work that also addresses what activities might in the future be located in the downtown area.

One approach to these discussions was to organize the work about goals of the university that have endured over the years – a commitment to academic excellence through a student-centered university, growing the academic program as human knowledge evolves, taking advantage of our DC location to serve the nation and the world, embracing the Jesuit educational heritage, serving our global academic ambitions, and enriching our liberal education tradition.

The group invented different future visions of what activities might be conducted on the Hilltop and what activities might be conducted downtown. One near-term issue was determining a location of the new McCourt School of Public Policy that maximizes the success of its mission as the first Public Policy school created in the 21st century. In that regard, discussions of synergies among McCourt and other schools of Georgetown took place. What location of the school best supports the interdisciplinary nature of a policy school? Will the future have more joint programs among our professional schools (Law, Business, Public Policy, Medicine, Continuing Studies)? What Georgetown educational and research activities are best placed near the government and research institutions in the city? How do we design space to maximize proximity of synergistic activities and minimize the harmful effects of multiple sites on cohesion of the university?

In essence, the group has performed some staff work for colleagues throughout the university. We will have discussions with larger groups of faculty and staff over the coming months, to gain new insights and ideas to guide these alternative visions.

It’s difficult to imagine a future 10 years from now, but failing to do so condemns us to a very constrained set of options. We don’t want this. Instead, we need the good ideas of the entire community to make wise decisions.

Statistics and the Real World

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The Founding Fathers of the United States were a group that valued the use of empirical data to guide decisions. In the constitution they chose to use a population census to re-align the House of Representatives every ten years to reflect the expected shifts and growth of population across the growing number of states. They increased the amount of information collected in that decennial census to inform the emerging new nation about the distribution of property ownership, occupational mixes, household conditions, etc.

Over the decades statistical information collected by Federal statistical agencies has formed the core information infrastructure of the country. It is the very cornerstone of the informed citizenry. It provides the information on how well we’re doing as a country. It informs us about how well the elected officials are doing in their leadership.

This infrastructure is valuable to the extent that it is objective, not affected by the political philosophy of the current elected officials. It’s valuable to the extent that it is an accurate portrayal of reality, using state of the art methods to collect data. It’s useful to the extent that it contains consistent indicators, comparable over time (to detect change in key phenomena). It’s helpful to the extent that it reflects key concerns of the society.

This infrastructure is a fragile one; the agencies that provide the objective information often must report that things are not going as well as those elected to office would hope they are. Over the years their budgets have suffered and some key statistical indicators have been dropped. In that sense, we know less than we did earlier.

These concerns arose recently with the current set of violent deaths involving police and African-American citizens. The last weeks have seen both citizen deaths and police deaths. FBI Director Comey, in a recent testimony to a Senate committee said, “We need more and better data related to officer-involved shootings and altercations with the citizens we serve, attacks against law enforcement officers, and criminal activity of all kinds.”

In the early 1970’s there was an effort to supplement police-reported crimes with a statistical series that was based on the notion that police-reported crimes were not accurate counts of events that violate laws. They were based on a reporting system internal to departments; they required the processing of descriptions of events that were likely to be judged as criminal violations by the justice system. There were many reasons that events were “unfounded,” deemed not reportable. To supplement these official reports, victimization survey methods were developed, that asked individual persons whether they had experienced what they thought was a criminate victimization, whether or not it was reported to the police.

But because of the relatively small size of the victimization surveys, relatively rare events are not well estimated. Again, Director Comey: “We in the FBI track and publish the number of “justifiable homicides” by police officers. But such reporting by police departments across the country is not mandatory, and perhaps lacks sufficient incentive, so not all departments participate. The result is that currently we cannot fully track incidents involving use of force by police. And while the ‘Law Enforcement Officers Killed and Assaulted’ report tracks the number of officers killed in the line of duty, we do not have a firm grasp on the numbers of officers assaulted in the line of duty. We cannot address concerns about officer-involved shootings if we do not know the circumstances surrounding such incidents.”

There are ongoing efforts to improve the consistency and content of police-reported criminal events. A new system of bottom-up reporting is in place but the rate of participation of local jurisdictions is lower than desirable. This prompted researchers to collect their own data from jurisdictions. The data come from only twelve jurisdictions among the thousands of jurisdictions in the country. They are jurisdictions that voluntarily cooperated. They do not represent in any statistically-meaningful way the full population.

In the absence of data that are strongly representative of the full population, it’s common that any data available will be used to draw conclusions about what is happening in our country. This is not always desirable. In this case, twelve jurisdictions form interesting case studies but solid conclusions about national phenomena need richer data. While the researchers should be credited with assembling such data, the nation really deserves consistent and comprehensive attention to assembling such statistical information.

Time has shown that this is best done with a Federal statistical agency that has strong devotion to data quality and complete objectivity.

Joint Appointment Initiative at Georgetown

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Every university is facing the challenge of how to increase the support of traditional disciplines, as they evolve, at the same time it invests in cross-disciplinary initiatives that have promise. Most of the existing reward systems of universities favor within-unit appointments, and hence presidents, provosts, and other leaders have been mounting special efforts at cross-unit appointments.

Last year, the three Executive Vice-Presidents (EVP’s), Ed Healton of the Medical Center, Bill Treanor of the Law Center, and I collaborated on a call for faculty proposals for joint appointments. This was a partnership to strengthen Georgetown by supporting cross-cutting scholarly and teaching activities, while at the same time seeking to attract the very best faculty to Georgetown.

In evaluating proposals we favored joint appointments between campuses/schools over joint appointments between units within the same school. Similarly, joint appointments between units with well-defined teaching/research synergies and those with jointly offered courses benefiting students in both units were favored over others. Finally, joint appointments entailing association with an existing interdisciplinary effort at Georgetown were preferred over others.

Last year, we redefined the joint appointment structure for the main campus to protect candidates from shouldering more than 100% jobs by their dual citizenship. We also specified a promotion review process that protected joint appointment holders (i.e., a positive outcome in one unit and a negative outcome in the other leads to a positive outcome in the first unit and a dropping of the joint appointment).

The joint appointment initiative succeeded in generating proposals from all three campuses and many different units at the university.

After input from all the schools, the following joint appointment searches have been approved for search in academic year 2016-2017:

Cross-campus Joint Searches

1. Department of Biology, Georgetown College and Department of Pathology, GU Medical Center: Non-Embryonic Stem Cell Biology

The biology of stem cells is an exciting research frontier that offers new insights and opportunities for understanding many basic processes, including aging, cancer and embryonic development. Indeed, the applications of stem cell biology to medicine are multifold and include uses for the prognosis, diagnosis and treatment of cancer, the treatment of age-related diseases, the treatment of genetically inherited diseases, and the regeneration of diseased or damaged tissues. Having our students exposed to this field is important for their preparation in several fields.

2. Department of Computer Science, Georgetown College and Georgetown Law: Information Privacy

Matters concerning data, privacy, and policy are central concerns that need systematic attention. Commercial collection of massive data sets, together with governments’ desire to obtain and use these data, raise serious concerns about both the privacy of the people represented in the data set as well as how these data may nonetheless be put to public purpose. The combination of legal scholars and computer scientists would be a strong one in this realm. Those on the policy side could specify how they wanted to use or share the data; the computer scientists could devise systems to allow it to happen, but provide strong guarantees that the data was not being used in other ways.

3. Graduate School of Arts and Sciences, College Department of Psychology, and the Medical Center Department of Neuroscience: Cognitive Aging

The world is facing a demographic shift sometimes called the “gray tsunami.” Due to increasing longevity, declining fertility rates, and population-control policies, the percent of the population over the age of 65 is increasing dramatically. Cognitive Aging is an umbrella term for the subfield within Aging that focuses on the individual’s mental factors in the context of aging. These include affective and cognitive processes, their brain bases, genetic and environmental influences, and effects on outcomes for adaptive functioning.

Cross-school Joint Searches

4. McCourt School of Public Policy and Department of Computer Science, Georgetown College: Policy Analytics

To enable sound data-based policymaking, society needs leaders trained in policymaking as well as data analysis on high-dimensional data. This is a set of skills that have historically appeared in separate programs – public policy and computer science. Recognizing the need for these interdisciplinary leaders, however, academic programs are beginning to appear that address the training needs for individuals who have a passion for this area. These programs include both aspects of policy analysis and data science. This appointment would be a key contributor to the “big data” initiatives at the McCourt School and strengthen the interdisciplinary impact of the computer science department.

5. McDonough School of Business and School of Foreign Service: International Business

To build on the recently approved joint master’s degree in International Business and Policy, this joint appointment would bring in a faculty member with a strong research agenda in the economic, strategic and political drivers of success for private sector and public sector organizations. This appointment would be a key catalyst to further the university goals of enhancing its global impact.

6. McDonough School of Business and Department of Computer Science, Georgetown College: Business Analytics

A senior hire in the area of Business Analytics would bring a strong research agenda in machine learning, Operations Research and Management, Business Information Systems, Business Analytics, Statistics, Econometrics, or other business related field. Possible areas of interest could include: utilizing large-scale data with data mining and machine learning to optimize business operations, algorithmic design for mathematical economics, mechanism design, optimization, game theory, or risk mitigation and analysis in complex networked systems such as business supply chains.
For all of these appointments, the search committees will seek to attract scholars with strong international reputations, who would add significantly to the stature of the Georgetown faculty, and who share a deep devotion to a student-centered research university.

On behalf of my two EVP colleagues, I thank all the faculty who reached across units to craft proposals for joint appointments. I congratulate the winning proposals and look forward to the process of identifying world-class faculty to add to the Georgetown community.

What’s Happening?

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A key attribute of a democracy is the belief that information flows to the citizenry must be ubiquitous, unfiltered, and continuous. This requirement must be executed by institutions that have a devotion to that enterprise. In the early days of the democracy, newspapers played one role in “keeping government officials honest.” Later, the development of quasi-independent government agencies totally devoted to providing objective, accurate information about the economy and the larger society spurred the information feedback loop.

We’re entering a new era, in my belief, in the nature of the feedback loop. New digital sources of data are now providing information on what’s happening. Sometimes it goes under the moniker of “what’s trending,” based either on Twitter traffic on given hashtags or on YouTube viewing counts. Some news commentators appear to treat the information in the same spirit that they treat a report on UN-coordinated cease-fire talks among several countries or the daily movement of the stock market.

If one reviews the history of survey research, there are three distinct streams of development – the use of surveys in journalism, the use of surveys in marketing, and the use of surveys for social scientific research. The use of surveys in journalism was a logical evolution of so-called “man-in-the-street” interviews (sorry, that’s what they called it at the time). These were viewed as useful supplements to a journalist’s investigation of some social or economic phenomenon of news interest. Such articles often began with the discussion of the event/status, then interweaved quotations from “real people” about how the phenomenon affected their lives. Such a literary form attempted to increase the “human interest” in the news. Of course, the journalist had complete control over choice of what “man-in-the-street” quotations to use, and thereby, what conclusions to prime among readers.

If one man-in-the-street interview was good, many were even better. Naïve assembly of many interviews arose, appearing to be more a “survey” of opinion than a single case-study. The news poll was born.

In a way focusing on trending tweets and popular YouTube videos is a modern version of the “man-in-the-street” interview. Some are presented as evidence of widely-shared attitudes in the public. They are compared to other trends to prompt conclusion about whether one issue is more important than another issue. They are often used as evidence that a specific event is important to the society.

Others are just silly and humorous diversions from the dreadful news of wars, abject poverty, murder, mayhem, and sadness.

What’s different about the “what’s trending” development is that it often doesn’t start with any hard news initiated by a journalist. The “man-in-the-street” is not an enriching feature of a hard news story; it is the story. The start and end of the story are popular hashtags and uploaded videos.

Because tracking hashtags is easier than doing man-in-the-street interviews, I suspect we will see more of this way of answering the question of “what’s happening.” I fear, however, that the citation of numbers (“100,000’s of uses of the hashtag in the last 12 hours,” “750,000 views of the video”) might be misinterpreted as having a value beyond what it deserves.

Every once in awhile, I’d like a commentator to tell us that, just because a few hundred thousand people are visibly behaving in some way, it may not tell us much of anything about all 323 million US residents or all 7 billion world residents. It’s quite frightening to consider the possibility that such information might be the only source for an informed citizenry to assess their welfare.

Dimensions of Knowledge

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All of us, through life, ponder about the balance between learning a little about a lot versus focusing our attention on learning more and more about a particular area.

Father Adolfo Nicholás, in a 2010 address, described the fear he has that modern life is overloaded with stimuli demanding our immediate attention. This overload breeds short attention spans. A short attention span produces a pervasive superficiality. It provides a breeding ground for fanaticism and ideologues. To counter this, he argued for “depth,” concentrated thinking and time for reflection as a way to release “creative imagination” to reassemble facts and observations into new understandings.

IBM has promoted the idea that their enterprise values “T-shape” people. By that it appears they mean experts in a subfield of knowledge who also are conversant in the basic concepts of many other fields. That basic knowledge is needed to work effectively in interdisciplinary teams. The base of the “T” is meant to graphically describe the extent of deep knowledge in the subfield, and the top of the “T” describes the many other fields in which basic knowledge is held.

In a completely different domain, some scholars speculate that what we interpret as wisdom is actually a synthesis of deep knowledge in an area and broad experience in many subfields. We sometimes encounter this in a mentor, who sees our situation from a vantage point different than ours, powered by their own years of experience. They diagnose a way forward for us, the mentee, that we could not see ourselves. We see it in an elder, who amazes us by putting together two seemingly disparate observations into a novel perspective. They have identified connections among facts and concepts to produce new insights.

This ability to synthesize information seems different from the notion of “depth” or the notion of “breadth” of knowledge. It is compatible with a metaphor used to describe visionaries – “height,” the ability to see solutions at a level that is superior to others. Visionaries “see above the crowd” because of their ability to synthesize lots of facts and combine them in new ways. The metaphor of height is popular because it communicates enhanced vision.

Thus, for real impact, the ability to synthesize diverse knowledge must accompany deep command of one field and broad competency in many. This synthesis provides the height of vision we so admire, leading to the creation of novel solutions based on the totality of knowledge.

How do universities achieve these goals? When we’re at our best, we present students with experiences that draw on deep and broad knowledge, but apply it to real world problems solvable only with new combinations of that knowledge. This is often a difficult task for students accustomed to highly structured teaching/learning protocols. It also challenges instructors to manage great uncertainties as students try to navigate problems that may not have a solution or may have multiple solutions. The move to experience-based learning often creates such experiences. Interdisciplinary problem-based studies also seem to offer fertile ground for rehearsing the synthesis step.

So, in essence, this is the argument for producing graduates who exhibit depth, breadth, and height. Instead of “T” people we need people that might be called “+” people.

Beneficence, Maleficence, and Instrumentalization in Data Ethics

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Two central notions in bioethics are “beneficence,” the provision of benefits to the patient, and the absence of “maleficence,” the “do no harm” principle. Certainly in constructing a framework for data ethics, these must also be central goals.

There doesn’t appear to be a perfect mapping of these ideas to statistical practice aimed at describing the attributes of large populations. IRB’s have largely adopted the practice that informed consent requires the participant’s understanding of both costs and benefits of their decision. For statistical information that benefits serve the common good not the individual, see last week’s blog, A Little More on Data Ethics.

Bioethics focuses on interventions (or lack thereof) on individuals. For example, medical procedures should be designed to benefit the individual.

Statistics for the common good seek beneficence for the whole population. Measuring the unemployment rate through self-reports of a sample of persons seeks to inform the citizenry of an indicator of the society’s well-being. Participants in employment surveys are promised that no action on themselves will be taken based on their responses. Statistical uses of data by definition are uninterested in the individual.

Further, not all statistical aggregations of data avoid maleficence for all persons. If the unemployment rate leads policy makers to introduce increased taxes to support the unemployed, then the relative socioeconomic status of employed persons is diminished. They, as a group, are harmed. In general, when data produce statistical information that leads to a reallocation of resources in a society, group harm results.

Thus, when individual data are used for statistical purposes, the interplay of individual versus group beneficence and maleficence is different than for the biomedical case.

When we move our attention to unobtrusive use of personal data, another concept seems useful for data ethics – instrumentalization. This is the use of other humans merely as a means to some other goal. One might consider this notion as relevant to informed consent. If researchers do not reveal their goals to the participant, the individual is not fully able to weigh costs and benefits of participation. Consent is then not “informed.” For example, users are routinely informed that their mobile phone positional data are used to provide traffic estimates. I have the right to refuse participation if I feel that I am merely being used as an instrument for a purpose that does not benefit me. Informed consent, in that sense, is the protection against instrumentalization in the researcher-participant relationship.

Such issues seem quite pertinent when the uses of the data are long-lasting and not visible to the participant. For example, I suspect that few users understand how their past internet behavior affects their current browsing experiences. The use of predictive models to guide the browser actions, based on user profile data, is often not easily discerned by a user. I suspect most users do not examine the displayed ads on a page as a reflection of their internet use, but as a mass-marketed effort for business development. Therefore, the benefit to the individual is increased by the intervention to the extent that the user finds the ads informative and useful. From one perspective, that is exactly the intent of the browser owner. To the extent that users click on ads, the browser’s statistical model has achieved the goal. One can easily make the argument that instrumentalization doesn’t seem to apply here (to the extent that the user read the privacy policy). If, on the other hand, the statistical model is not well formulated, and ads presented are annoyances, does instrumentalization arise? (Such an occurrence prompts the need for the user to opt-out of the service under those circumstances.)

As we think about how to build a sustainable environment for common good uses of large digital data resources, we must address our ethical obligations to those providing the data. I suspect we’ll be talking about beneficence, maleficence, and instrumentalization in the future.

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