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Deepfakes, Forensic Science, and Police Investigations

By Joseph Schafer

USA Today recently ran a piece on the emergence of “deepfakes”

Deepfakes is a term applied to the ability to manipulate video to modify words and possible actions. In other words, to take something that is ostensibly real and modify it in such a way that the video conveys something entirely different. The implications for policing, while they might seem distant and rare, are profound, particularly when coupled with social media and a 280-character news cycle based on short attention spans and limited critical evaluation of sources.

The technology is being advanced, in part, by entertainment media. Video of an actor might be modified in post-production to correct an error or insert a better joke. An actor who has died can still complete their appearance in a film or TV show (although there might be legal, contractual, and financial implications).

Consider this technology in the hands of a foreign nation, however. Just days before an election, video might be released that seems to show a candidate making a particular statement. The capacity to interfere with free elections is profound and the risk in upcoming election cycles is astonishingly real. What was a pipe-dream in 2016 increasingly appears to be a reality for 2020.

In time, the risks here will not be limited to entertainment media or nations leveraging influence campaigns against each other. Imagine controversial police use of force event captured by a bystander’s mobile phone. In the near future, it might be possible to manipulate that video to make it appear the officer made biased, vulgar, or profane statements. In time, it might be possible to manipulate the video even more, to edit out citizen resistance or elevate the apparent force used by an officer.

In all of these examples, is anyone calling for the development of forensic expertise to analyze video and determine manipulation has taken place? Do crime labs and investigative agencies employ personnel with the requisite skill set for such analysis? How long will it take to develop credentialing standards for such forensic examiners? Will society care, or label reports that video has been altered “fake news”, continuing to believe that what they saw in a video with their own eyes represents reality?

Questions abound, but answers and solutions (for now) appear elusive. As future thinking police leaders, are we doing enough to call for attention and action on this issue before matters escalate beyond mitigation?


fear, crime and terrorism in the u.s.

bud levin

we have long known that there is little relationship between crime rate and people’s fear of crime. facts don’t matter very much. (e.g.,

a recent RAND publication reminds us that terrorism has declined.
“…an overall decline of terrorism in the West since the 1970s.
These findings suggest that the threat of terrorism should not affect individuals’ behavior in the United States and Western Europe-not even in the wake of a significant terrorist event.”( )

faint hope, that. fear of terrorism remains high (
implication: if we focus merely on terrorism- and crime-fighting we will be missing the reassurance that many in our population seek. they seek a perception of “safety” rather than absence of terrorism and crime.

on the up side, if people were rational, we wouldn’t need many cops.

What Will Police Do With Ubiquitous Information?

bud levin

the author makes a good argument — that in a cashless society, we (public and private sectors) will have information on nearly every detail of people’s lives. cash inevitably will be, as the author says, supplanted by information — and to a considerable extent already is.

the arguments will make the current fbi vs apple sort of argument seem rather penny ante. police — or private sector surrogates — will have comprehensive information about everyone’s lives, including those of other police.

what is clear is that the potential for “enemy of the state” on steroids is real. what is not clear is what police will do with that information.

how could — or should — law enforcement (and police) prepare for this probable future?

Data on Police Use of Force

bud levin

View at

nick gives an example of how one might properly analyse data. department-wide data usually are not very helpful. the devil — and the opportunity for improvement — are in the details, in crosstabs, in demographics, in ……

gross averages hide more than they reveal.

imagine police departments that had crime analysts, or analysts of any sort, who had the statistical and scientific chops to collect and crunch the numbers in a meaningful way instead of in a way intended to garner (or combat) headlines.

of course, that would require a lot of imagination. few chiefs can afford to hire such folks. but wouldn’t it be interesting if analysis were to supplant politicized and uninformed argument?

How do we get off this train?

Most of us do not live in abundant riches. Our nation, our states and our cities are confronted with problems and limited resources to throw at them. For every dollar thrown at a problem, there is some alternative use of that dollar that didn’t get funded. Economists call this opportunity cost. Among the many benefits of foresight for  public policy, an awareness of how trends may intersect in the future may prevent us from wasting scarce resources funding projects that will lose their value prematurely.

Recently, I’ve been doing some research on self-driving vehicles (SDVs).  Along the way, I’ve developed a strengthening sense that two trends that are headed for collision.

  1. SDVs seem to be the best bet for achieving Personal Rapid Transit (PRT), primarily through car-share and for-hire models (Uber, Zipcar, Lyft, etc.)  Even SDVs that are individually owned may be monetized during down time by loaning them to a share service.  Except perhaps for those who reside directly on transit routes, PRT is a superior option relative to mass rapid transit (MRT).   PRT will deliver the person from origin to destination via the most optimal route, minimizing waiting and eliminating transfers.
  2. Cities are spending billions on light rail installations.  For example, Houston recently expanded its rail system by adding a North line and a Southeast line at estimated costs of $143M and $125M per mile respectively.  An analysis in the Houston Chronicle estimated the cost of 8.9 miles of rail at $1.4B (  Because buses operate on public roadways, bus-based MRT is flexible and can more easily adapt to need. But rail-based MRT is much more capital intensive, requiring expensive infrastructure to operate. Because of the capital involved, rail-based MRT projects are major bets with time horizons in excess of 30 years.

I also have two hunches or assumptions about the impact of car share models on the future:

  1. They will provide an alternative to car ownership for the poor, even in transit-weak cities;
  2. Because of 1), they will accelerate the adoption curve for SDVs by eliminating the back-end of the traditional vehicle life cycle.

While the earliest models are coming on-line now (Tesla, 2017 Mercedes E-Class), I think fleet models (like Google) will roll-out around 2020 in the first cities (San Francisco, Austin, etc).  I expect most luxury brands to roll-out SDV capabilities around 2020 and mainstream brands to follow around 2025.  If there were no changes in car ownership patterns, half-the vehicles in service will turn over in 11 years and most will be out of service in 15.  However, viable and cost-effective SDV car-share fleets could eliminate the need for the poor to own a vehicle and secondary car markets (used cars) could take a shock.  This would shorten the life-spans of non-SDV stock.  It is plausible that the public fleet could become majority SDV around 2030.

If SDVs realized the potential of PRT, then what will keep MRT ridership up, particularly on the fixed routes of light rail?  All the cities making light rail investments presumably are anticipating system lifespans beyond 15-20 years, but SDV delivered PRT could threaten those systems within that period. At great cost to society, light rail systems may lose economic viability prematurely. When cities are paying for expensive light rail projects long after PRT has taken their riders away, there will be fewer resources for public safety.  Urban planners need to keep in mind the potential impacts of SDVs when making grand pitches for rail.

Policing: Numbers versus Relationships

Bud Levin

the above is a nice article describing versions of “predictive policing.”  however, the underlying problem is not the details of software but the tension between policing by the numbers and policing by relationships.
traditional policing has valued numbers, even though we haven’t necessarily paid a lot of attention to them as we work day-to-day. some of us have paid a lot of attention to relationships while others not so much, focusing more on “catching bad guys.”
to what extent is that tension driving ambivalence among officers — “productivity” versus relationship-building. is there yet a department that validly quantifies relationship-building?  or does it remain as ill-defined as pornography, “we know it when we see it?”
moving forward, does what we measure comport well with what we are trying to do? if not, does measurement matter? how do we move forward?

Using Community Policing to Prevent Violent Extremism

Bud Levin

The task, preventing violent extremism, reminds one of “Who knows what evil lurks in the hearts of men?” While Lamont Cranston might have known, for the rest of us the task remains foreboding.

Any of us should be grateful when simple, understandable and credible hope is put forth. Schanzer et al. have done us that favor. Still, the limits — mostly as laid out by the authors — should be understood.

These are “promising.” We’ve seen promises evaporate in other contexts. These are not easy to pull off. And the barriers to success are non-trivial.