All posts in category scholarly

What to show in your tech resume?

Jason Brinkley on LinkedIn the other day had a comment on the common look of resumes – I disagree with his point in part but it is worth a blog post to say why:

So first, when giving advice I try to be clear about what I think are just my idiosyncratic positions vs advice that I feel is likely to generalize. So when I say, you should apply to many positions, because your probability of landing a single position is small, that is quite general advice. But here, I have personal opinions about what I want to see in a resume, but I do not really know what others want to see. Resumes, when cold applying, probably have to go through at least two layers (HR/recruiter and the hiring manager), who each will need different things.

People who have different colored resumes, or in different formats (sometimes have a sidebar) I do not remember at all. I only care about the content. So what do I want to see in your resume? (I am interviewing for mostly data scientist positions.) I want to see some type of external verification you actually know how to code. Talk is cheap, it is easy to list “I know these 20 python libraries” or “I saved our company 1 million buckaroos”.

So things I personally like seeing in a resume are:

  • code on github that is not a homework assignment (it is OK if unfinished)
  • technical blog posts
  • your thesis! (or other papers you were first/solo author)

Very few people have these things, so if you do and you land in my stack, you are already at the like 95th percentile (if not higher) for resumes I review for jobs.

The reason having outside verification you actually know what you are doing is because people are liars. For our tech round, our first question is “write a python hello world program and execute it from the command line” – around half of the people we interview fail this test. These are all people who list they are experts in machine learning, large language models, years of experience in python, etc.

My resume is excessive, but I try to practice what I preach (HTML version, PDF version)

I added some color, but have had recruiters ask me to take it off the resume before. So how many people actually click all those links when I apply to positions? Probably few if any – but that is personally what I want to see.

There are really only two pieces of advice I have seen repeatedly about resumes that I think are reasonable, but it is advice not a hard rule:

  • I have had recruiters ask for specific libraries/technologies at the top of the resume
  • Many people want to hear about results for project experience, not “I used library X”

So while I dislike the glut of people listing 20 libraries, I understand it from the point of a recruiter – they have no clue, so are just trying to match the tech skills as best they can. (The matching at this stage I feel may be worse than random, in that liars are incentivized, hence my insistence on showing actual skills in some capacity.) It is infuriating when you have a recruiter not understand some idiosyncratic piece of tech is totally exchangeable with what you did, or that it is trivial to learn on the job given your prior experience, but that is not going to go away anytime soon.

I’d note at Gainwell we have no ATS or HR filtering like this (the only filtering is for geographic location and citizenship status). I actually would rather see technical blog posts or personal github code than saying “I saved the company 1 million dollars” in many circumstances, as that is just as likely to be embellished as the technical skills. Less technical hiring managers though it is probably a good idea to translate technical specs to more plain business implications though.

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by apwheele on November 1, 2025  •  Permalink
Posted in data science, Personal Productivity, Python, scholarly
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Posted by apwheele on November 1, 2025

https://andrewpwheeler.com/2025/11/01/what-to-show-in-your-tech-resume/

Recommend reading The Idea Factory, Docker python tips

A friend recently recommended The Idea Factory: Bell Labs and the Great Age of American Innovation by Jon Gertner. It is one of the best books I have read in awhile, so also want to recommend to the readers of my blog.

I was vaguely familiar with Bell Labs given my interest in stats and computer science. John Tukey makes a few honorable mentions, but Claude Shannon is a central character of the book. What I did not realize is that almost all of modern computing can be traced back to innovations that were developed at Bell Labs. For a sample, these include:

  • the transistor
  • fiber optic cables (I did not even know, fiber is very thin strands of glass)
  • the cellular network with smaller towers
  • satellite communication

And then you get smattering of different discussions as well, such as the material science that goes into making underwater cables durable and shark resistant.

The backstory was that AT&T in the early 20th century had a monopoly on landline telephones. Similar now to how most states have a single electric provider – they were a private company but blessed by the government to have that monopoly. AT&T intentionally had a massive research arm that they used to improve communications, but also they provided that research back into the public coffers. Shannon was a pure mathematician, he was not under the gun to produce revenue.

Gertner basically goes through a series of characters that were instrumental in developing some of these ideas, and in creating and managing Bell Labs itself. It is a high level recounting of Gertner mostly from historical notebooks. One of the things I really want to understand is how institutions even tackle a project that lasts a decade – things I have been involved in at work that last a year are just dreadful due to transaction costs between so many groups. I can’t even imagine trying to keep on schedule for something so massive. So I do not get that level of detail from the book, just moreso someone had an idea, developed a little tinker proof of concept, and then Bell Labs sunk a decade an a small army of engineers to figure out how to build it in an economical way.

This is not a critique of Gertner (his writing is wonderful, and really gives flavor to the characters). Maybe just sinking an army of engineers on a problem is the only reasonable answer to my question.

Most of the innovation in my field, criminal justice, is coming from the private sector. I wonder (or maybe hope and dream is a better description) if a company, like Axon, could build something like that for our field.

Part of the point for writing blog posts is that I do the same tasks over and over again. Having a nerd journal is convenient to reference.

One of the things that I do not have to commonly do, but it seems like once a year at my gig, I need to putz around with Docker containers. For note for myself, when building python apps, to get the correct caching you want to install the libraries first, and then copy the app over.

So if you do this:

FROM python:3.11-slim
COPY . /app
RUN pip install --no-cache-dir -r /app/requirements.txt
CMD ["python", "main.py"]

Everytime you change a single line of code, you need to re-install all of the libraries. This is painful. (For folks who like uv, this does not solve the problem, as you still need to download the libraries everytime in this approach.)

A better workflow then is to copy over the single requirements.txt file (or .toml, whatever), install that, and then copy over your application.

FROM python:3.11-slim
COPY requirements.txt ./
RUN pip install --no-cache-dir -r requirements.txt
COPY . /app
CMD ["python", "main.py"]

So now, only when I change the requirements.txt file will I need to redo that layer.

Now I am a terrible person to ask about dev builds and testing code in this set up. I doubt I am doing things the way I should be. But most of the time I am just building this.

docker build -t py_app .

And then I will have logic in main.py (or swap out with a test.py) that logs whatever I need to the screen. Then you can either do:

docker run --rm py_app

Or if you want to bash into the container, you can do:

docker run -it --rm py_app bash

Then from in the container you can go into the python REPL, edit a file using vim if you need to, etc.

Part of the reason I want data scientists to be full stack is because at work, if I need another team to help me build and test code, it basically adds 3 months at a minimum to my project. Probably one of the most complicated things myself and team have done at the day job is figure out the correct magical incantations to properly build ODBC connections to various databases in Docker containers. If you can learn about boosted models, you can learn how to build Docker containers.

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by apwheele on September 2, 2025  •  Permalink
Posted in data science, scholarly
Tagged

Posted by apwheele on September 2, 2025

https://andrewpwheeler.com/2025/09/02/recommend-reading-the-idea-factory-docker-python-tips/

Deep research and open access

Most of the major LLM chatbot vendors are now offering a tool called deep research. These tools basically just scour the web given a question, and return a report. For academics conducting literature reviews, the parallel is obvious. We just tend to limit the review to peer reviewed research.

I started with testing out Google’s Gemini service. Using that, I noticed almost all of the sources cited were public materials. So I did a little test with a few prompts across the different tools. Below are some examples of those:

  • Google Gemini question on measuring stress in police officers (PDF, I cannot share this chat link it appears)
  • OpenAI Effectiveness of Gunshot detection (PDF, link to chat)
  • Perplexity convenience sample (PDF, Perplexity was one conversation)
  • Perplexity survey measures attitudes towards police (PDF, see chat link above)

The report on officer mental health measures was an area I was wholly unfamiliar. The other tests are areas where I am quite familiar, so I could evaluate how well I thought each tool did. OpenAI’s tool is the most irksome to work with, citations work out of the box for Google and Perplexity, but not with ChatGPT. I had to ask it to reformat things several times. Claude’s tool has no test here, as to use its deep research tool you need a paid account.

Offhand each of the tools did a passable job of reviewing the literature and writing reasonable summaries. I could nitpick things in both the Perplexity and the ChatGPT results, but overall they are good tools I would recommend people become familiar with. ChatGPT was more concise and more on-point. Perplexity got the right answer for the convenience sample question (use post-stratification), but also pulled in a large literature on propensity score matching (which is only relevant for X causes Y type questions, not overall distribution of Y). Again this is nit-picking for less than 5 minutes of work.

Overall these will not magically take over writing your literature review, but are useful (the same way that doing simpler searches in google scholar is useful). The issue with hallucinating citations is mostly solved (see the exception for ChatGPT here). You should consult the original sources and treat deep research reports like on-demand Wikipedia pages, but lets not kid ourselves – most people will not be that thorough.

For the Gemini report on officer mental health, I went through quickly and broke down the 77 citations across the publication type or whether the sources were in HTML or PDF. (Likely some errors here, I went by the text for the most part.) For the HTML vs PDF, 59 out of 77 (76%) are HTML web-sources. Here is the breakdown for my ad-hoc categories for types of publications:

  • Peer Review (open) – 39 (50%)
  • Peer review (just abstract) 10 (13% – these are all ResearchGate)
  • Open Reports 23 (30%)
  • Web pages 5 (6%)

For a quick rundown of these. Peer reviewed should be obvious, but sometimes the different tools cite papers that are not open access. In these cases, they are just using the abstract to madlib how Deep Research fills in its report. (I consider ResearchGate articles here as just abstract, they are a mix of really available, but you need to click a link to get to the PDF in those cases. Google is not indexing those PDFs behind a wall, but the abstract.) Open reports I reserve for think tank or other government groups. Web pages I reserve for blogs or private sector white papers.

I’d note as well that even though it does cite many peer review here, many of these are quite low quality (stuff in MDPI, or other what look to me pay to publish locations). Basically none of the citations are in major criminology journals! As I am not as familiar with this area this may be reasonable though, I don’t know if this material is often in different policing journals or Criminal Justice and Behavior and just not being picked up at all, or if that lit in those places just does not exist. I have a feeling it is missing a few of the traditional crim journal sources though (and picks up a few sources in different languages).

The OpenAI report largely hallucinated references in the final report it built (something that Gemini and Perplexity currently do not do). The references it made up were often portmanteaus of different papers. Of the 12 references it provided, 3 were supposedly peer reviewed articles. You can in the ChatGPT chat go and see the actual web-sources it used (actual links, not hallucinated). Of the 32 web links, here is the breakdown:

  • Pubmed 9
  • The Trace 5
  • Kansas City local news station website 4
  • Eric Piza’s wordpress website 3
  • Govtech website 3
  • NIJ 2

There are single links then to two different journals, and one to the Police Chief magazine. I’d note Eric’s site is not that old (first RSS feed started in February 2023), so Eric making a website where he simple shares his peer reviewed work greatly increased his exposure. His webpage in ChatGPT is more influential than NIJ and peer reviewed CJ journals combined.

I did not do the work to go through the Perplexity citations. But in large part they appear to me quite similar to Gemini on their face. They do cite pure PDF documents more often than I expected, but still we are talking about 24% in the Gemini example are PDFs.

The long story short advice here is that you should post your preprints or postprints publicly, preferably in HTML format. For criminologists, you should do this currently on CrimRXiv. In addition to this, just make a free webpage and post overviews of your work.

These tests were just simple prompts as well. I bet you could steer the tool to give better sources with some additional prompting, like “look at this specific journal”. (Design idea if anyone from Perplexity is listening, allow someone to be able to whitelist sources to specific domains.)

Other random pro-tip for using Gemini chats. They do not print well, and if they have quite a bit of markdown and/or mathematics, they do not convert to a google document very well. What I did in those circumstances was to do a bit of javascript hacking. So go into your dev console (in Chrome right click on the page and select “Inspect”, then in the new page that opens up go to the “Console” tab). And depending on the chat browser currently opened, can try entering this javascript:

// Example printing out Google Gemini Chat
var res = document.getElementsByTagName("extended-response-panel")[0];
var report = res.getElementsByTagName("message-content")[0];
var body = document.getElementsByTagName("body")[0];
let escapeHTMLPolicy = trustedTypes.createPolicy("escapeHTML", {
 createHTML: (string) => string
});
body.innerHTML = escapeHTMLPolicy.createHTML(report.innerHTML);
// Now you can go back to page, cannot scroll but
// Ctrl+P prints out nicely

Or this works for me when revisiting the page:

var report = document.getElementById("extended-response-message-content");
var body = document.getElementsByTagName("body")[0];
let escapeHTMLPolicy = trustedTypes.createPolicy("escapeHTML", {
 createHTML: (string) => string
});
body.innerHTML = escapeHTMLPolicy.createHTML(report.innerHTML);

This page scrolling does not work, but Ctrl + P to print the page does.

The idea behind this, I want to just get the report content, which ends up being hidden away in a mess of div tags, promoted out to the body of the page. This will likely break in the near future as well, but you just need to figure out the correct way to get the report content.

Here is an example of using Gemini’s Deep Research to help me make a practice study guide for my sons calculus course as an example.

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by apwheele on August 28, 2025  •  Permalink
Posted in Criminal Justice, Papers, Personal Productivity, scholarly
Tagged ,

Posted by apwheele on August 28, 2025

https://andrewpwheeler.com/2025/08/28/deep-research-and-open-access/

Follow up on Reluctant Criminologists critique of build stuff

Jon Brauer and Jake Day recently wrote a response to my build stuff post, Should more criminologists build stuff on their Reluctant Criminologists blog. Go ahead and follow Jon’s and Jake’s thoughtful work. They asked for comment before posting – I mainly wanted to post my response to be more specific about “how much” I think criminologists should build stuff. (Their initial draft said I should “abandon” theoretical research, which is not what I meant (and they took out before publishing), but could see how one could be confused by my statement “emphasis should he flipped” after saying near 0% of work now is building stuff.)

So here is my response to their post:

To start I did not say abandon theoretical research, I said “the emphasis be on doing”. So that is a relative argument, not an absolute. It is fine to do theoretical work, and it is fine to do ex-ante policy evaluations (which should be integrated into the process of building things, seeing if something works well enough to justify its expense I would say is a risky test). I do not have a bright line that I think building stuff is optimal for the field, but it should be much more common than it is now (which is close to 0%). To be specific on my personal opinion, I do think “build stuff” should be 50%+ of research criminologists’ time (relative to writing papers).

I am actually more concerned with the larping idea I gave. You have a large number of papers in criminology that justify their motivation not really as theoretical, but as practical to operations. And they are just not even close. So let’s go with the example of precise empirical distributions of burglaries at the neighborhood level. (It is an area I am familiar with, and there are many “I have a new model for crime in space” papers.) Pretend I did have a forecast, and I said there are going to be 10 burglaries in your neighborhood next month. What exactly are you supposed to do with that information? Forecasting the distribution does not intrinsically make it obvious how to prevent crime (nature does not owe us things we can manipulate). Most academic criminologists would say it is useful for police allocation, which is so vague as to be worthless.

You also do not need a fully specified causal chain to prevent crime. Most of the advancement in crime prevention looks more like CPTED applications than understanding “root causes” (which that phrase I think is a good example of an imprecise theory). I would much rather academics try to build specific CPTED applications than write another regression paper on crime and space (even if it is precise).

For the dark side part, in the counterfactual world in which academics don’t focus on direct applications, it does not mean those applications do not get built. They just get built by people who are not criminologists. It was actually the main reason I wrote the post – folks are building things now that should have more thoughtful input from academic criminologists.

For a specific example, different tech companies are demo’ing products with the ultimate goal of improving police officers mental health. These include flagging if officers go to certain types of calls too often, or using a chatbot as a therapist. Real things I would like criminologists like yourselves being involved in product development, so you can say “How do we know this is actually improving the mental health of officers?”. I vehemently disagree that more academic criminologists being involved will make development of these applications worse.

The final part I want to say is that apps need not intrinsically be focused on anything. I gave examples in policing that I am aware of, because that is my stronger area of expertise, but it can be anything. So let’s go with personal risk assessments. Pre-trial, parole/probation risk assessments look very similar to what Burgess built 100 years ago at this point. So risk stratification is built on the idea that you need to triage resources (some people need more oversight, some less), especially for the parole scenario. Now it is certainly feasible someone comes up with a better technological solution that risk stratification is not needed at all (say better sensors or security systems that obviate the need for the more intensive human oversight). Or a more effective regimen that applies to everyone, say better dynamic risk assessments, so people are funneled faster to more appropriate treatment regimes than just having a parole officer pop in from time to time.

I give this last example because I think it is a an area where focusing on real applications I suspect will be more fruitful long term for theory development. So we have 100 years and thousands of papers on risk assessment, but really only very incremental progress in that area. I believe a stronger focus on actual application – thinking about dynamic measures to accomplish specific goals (like the treatment monitoring and assignment), is likely to be more fruitful than trying to pontificate about some new theory of man that maybe later can be helpful.

We don’t have an atom to reduce observations down to (nor do we have an isolated root node in a causal diagram). We are not going to look hard enough and eventually find Laplace’s Demon. Focusing on a real life application, how people are going to use the information in practice, I think is a better way for everyone to frame their scientific pursuits. It is more likely a particular application changes how we think about the problem all together, and then we mold the way we measure to help accomplish that specific task. Einstein just started with the question “how do we measure how fast things travel when everything is moving”, a very specific question. He did not start out by saying “I want a theory of the universe”.

I am more bullish on real theoretical breakthroughs coming from more mundane and practical questions like “how do we tell if a treatment is working” or “how do we know if an officer is having a mental health crisis” than I am about someone coming up with a grander theory of whatever just from reading peer reviewed papers in their tower.

And here is Jon’s response to that:

Like you, we try to be optimistic, encouraging, and constructive in tone, though at times it requires serious effort to keep cynicism at bay. In general, if we had more Andrew Wheeler’s thoughtfully building things and then evaluating them, then I agree this would be a good thing. Yet, if I don’t trust someone enough to meaningfully observe, record, and analyze the gauges, then I’m certainly not going to trust them to pilot – or to understand well enough to successfully build and improve upon the car/airplane/spaceship. Meanwhile, the normative analysis is that everything is significant/everything works – unless it’s stuff we collectively don’t like. In that context, the cynic in me things we are better off of we simply focus on teaching many (most?) social scientists to observe and analyze better – and may even do less harm despite wasted resources by letting them larp.

Jon and Jake do not have a an estimate in their post on what they think the mix should be building vs theorizing (they say pluralist in the post). I think the near 0 we do now is not good.

Much of this back and forth tends to mirror the current critique of advocacy in science. The Charles Tittle piece they cite, The arrogance of public sociology, could have been written yesterday.

Both the RC group and Tittle’s have what I would consider a perfect enemy of the good argument going on. People can do bad work, people can do good work. I want folks to go out and do good, meaningful work. I have met plenty of criminologists (and the flipside the level of competence of many software engineers) to not have RC’s level of cynicism.

As an individual, I don’t think it makes much sense to worry about the perception of the field as a whole. I cannot control my fellow criminologists, I can only control what I personally do. Tittle in his critique thought public sociology would erode any legitimacy of the field. He maybe was right, but I posit producing mostly irrelevant work will put criminology on the same path.

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by apwheele on June 18, 2025  •  Permalink
Posted in Crime Analysis, Criminal Justice, scholarly
Tagged

Posted by apwheele on June 18, 2025

https://andrewpwheeler.com/2025/06/18/follow-up-on-reluctant-criminologists-critique-of-build-stuff/

Build Stuff

I have had this thought in my head for a while – criminology research to me is almost all boring. Most of the recent advancement in academia is focused on making science more rigorous – more open methods, more experiments, stronger quasi-experimental designs. These are all good things, but to me still do not fundamentally change the practical implementation of our work.

Criminology research is myopically focused on learning something – I think this should be flipped, and the emphasis be on doing something. We should be building things to improve the crime and justice system.

How criminology research typically goes

Here is a screenshot of the recent articles published in the Journal of Quantitative Criminology. I think this is a pretty good cross-section of high-quality, well-respected research in criminology.

Three of the four articles are clearly ex-ante evaluations of different (pretty normal) policies/behavior by police and their subsequent downstream effects on crime and safety. They are all good papers, and knowing how effective a particular policy works (like stop and frisk, or firearm seizures) are good! But they are the literal example where the term ivory tower comes from – these are things happening in the world, and academics passively observe and say how well they are working. None of the academics in those papers were directly involved in any boots on the ground application – they were things normal operations the police agencies in question were doing on their own.

Imagine someone said “I want to improve the criminal justice system”, and then “to accomplish this, I am going to passively observe what other people do, and tell them if it is effective or not”. This is almost 100% of what academics in criminology do.

The article on illicit supply chains is another one that bothers me – it is sneaky in the respect that many academics would say “ooh that is interesting and should be helpful” given its novelty. I challenge anyone to give a concrete example of how the findings in the article can be directly useful in any law enforcement context. Not hypothetical, “can be useful in targeting someone for investigation”, like literal “this specific group can do specific X to accomplish specific Y”. We have plenty of real problems with illicit supply chains – drug smuggling in and out of the US (recommend the contraband show on Amazon, who knew many manufactures smuggle weed from US out to the UK!). Fentanyl or methamphetamine production from base materials. Retail theft groups and selling online. Plenty of real problems.

Criminology articles tend to be littered with absurdly vague accusations that they can help operations. They almost always cannot.

So we have articles that are passive evaluations of policies other people thought up. I agree this is good, but who exactly comes up with the new stuff to try out? We just have to wait around and hope other people have good ideas and take the time to try them out. And then we have theoretical articles larping as useful in practice (since other academics are the ones reviewing the papers, and no one says “erm, that is nice but makes no sense for practical day to day usage”).

Some may say this is the way science is supposed to work. My response to that is I don’t know dude, go and look at what folks are doing in the engineering or computer science or biology department. They seem to manage both theoretical and practical advancements at the same time just fine and dandy.

Well what have you built Andy?

It is a fair critique if you say “most of your work is boring Andy”. Most of my work is the same “see how a policy works from the ivory tower”, but a few are more “build stuff”. Examples of those include:

In the above examples, the one that I know has gotten the most traction are simple rules to identify crime spikes. I know because I have spent time demonstrating that work to various crime analysts across the country, and so many have told me “I use your Poisson Z-score Andy”. (A few have used the patrol area work as well, so I should be in the negative for carbon generation.)

Papers are not what matter though – papers are a distraction. The applications are what matter. The biggest waste currently in academic criminology work is peer reviewed papers. Our priorities as academics are totally backwards. We are evaluated on whether we get a paper published, we should be evaluated on whether we make the world a better place. Papers by themselves do not make the world a better place.

Instead of writing about things other people are doing and whether they work, we should spend more of our time trying to create things that improve the criminal justice system.

Some traditional academics may not agree with this – science is about formulating and testing hypotheses. This need not be in conflict with doing stuff. Have a theory about human nature, what better way to prove the theory than building something to attempt to change things for the better according to your theory. If it works in real life to accomplish things people care about guess what – other people will want to do it. You may even be able to sell it.

Examples of innovations I am excited about

Part of what prompted this was I was talking to a friend, and basically none of the things we were excited about have come from academic criminologists. I think a good exemplar of what I mean here is Anthony Tassone, the head of Truleo. To be clear, this is not a dig but a compliment, following some of Anthony’s posts on social media (LinkedIn, X), he is not a Rhodes Scholar. He is just some dude, building stuff for criminal justice agencies mostly using the recent advancements in LLMs.

For a few other examples of products I am excited about how they can improve criminal justice (I have no affiliations with these beyond I talk to people). Polis for evaluating body worn camera feeds. Dan Tatenko for CaseX is building an automated online crime reporting system that is much simpler to use. The folks at Carbyne (for 911 calls) are also doing some cool stuff. Matt White at Multitude Insights is building a SaaS app to better distribute BOLOs.

The folks at Polis (Brian Lande and Jon Wender) are the only two people in this list that have anything remotely to do with academic criminology. They each have PhDs (Brian in sociology and Jon in criminology). Although they were not tenure track professors, they are former/current police officers with PhDs. Dan at CaseX was a detective not that long ago. The folks at Carbyne I believe are have tech backgrounds. Matt has a military background, but pursued his start up after doing an MBA.

The reason I bring up Anthony Tassone is because when we as criminologists say we are going to passively evaluate what other people are doing, we are saying “we will just let tech people like Anthony make decisions on what real practitioners of criminal justice pursue”. Again not a dig on Anthony – it is a good thing for people to build cool stuff and see if there is a market. My point is that if Anthony can do it, why not academic criminologists?

Rick Smith at Axon is another example. While Axon really got its dominate market due to conducted energy devices and then body worn cameras (so hardware), quite a bit of the current innovation at Axon is software. And Rick did not have a background in hardware engineering either, he just had an idea and built it.

Transferring over into professional software engineering since 2020, let me tell my fellow academics, you too can write software. It is more about having a good idea that actually impacts practice.

Where to next?

Since the day gig (working on fraud-waste-abuse in Medicaid claims) pays the bills, most of my build stuff is now focused on that. The technical skills to learn software engineering are currently not effectively taught in Criminal Justice PhD programs, but they could be. Writing a dissertation is way harder than learning to code.

While my python book has a major focus on data analysis, it is really the same skills to jump to more general software engineering. (I specifically wrote the book to cover more software engineering topics, like writing functions and managing environments, as most of the other python data science books lack that material.)

Skills gap is only part of the issue though. The second is supporting work that pursues building stuff. It is really just norms in the current academe that stop this from occurring now. People value papers, NIJ (at least used to) mostly fund very boring incremental work.

I discussed start ups (people dreaming and building their own stuff) and other larger established orgs (like Axon). Academics are in a prime position to pursue their own start ups, and most Universities have some support for this (see Joel Caplan and Simsi for an example of that path). Especially for software applications, there are few barriers. It is more about time and effort spent pursuing that.

I think the more interesting path is to get more academic criminologists working directly with software companies. I will drop a specific example since I am pretty sure he will not be offended, everyone would be better off if Ian Adams worked directly for one of these companies (the companies, Ian’s take home pay, long term advancement in policing operations). Ian writes good papers – it would be better if Ian worked directly with the companies to make their tools better from the get go.

My friend I was discussing this with gave the example of Bell Labs. Software orgs could easily have professors take part time gigs with them directly, or just go work with them on sabbaticals. Axon should support something like that now.

While this post has been focused on software development, I think it could look similar for collaborating with criminal justice agencies directly. The economics will need to be slightly different (they do not have quite as much expendable capital to support academics, the ROI for private sector I think should be easily positive in the long run). But that I think that would probably be much more effective than the current grant based approach. (Just pay a professor directly to do stuff, instead of asking NIJ to indirectly support evaluation of something the police department has decided to already put into operation.)

Scientific revolutions are not happening in journal articles. They are happening by people building stuff and accomplishing things in the real world with those innovations.

For a few responses to this post, Alex sent me this (saying my characterization of Larry as passively observing is not quite accurate), which is totally reasonable:

Nice post on building/ doing things and thanks for highlighting the paper with Larry. One error however, Larry was directly involved in the doing. He was the chief science officer for the London Met police and has designed their new stop and frisk policy (and targeting areas) based directly on our work. Our work was also highlighted by the Times London as effective crime policy and also by the Chief of the London Met Police as well who said it was one of the best policy relevant papers he’s ever seen. All police are now being by trained on the new legislation on stop and search in procedurally just ways. You may not have known this background but it’s directly relevant to your post.

Larry Sherman (and David Weisburd), and their work on hot spots + direct experiments with police are really exemplars of “doing” vs “learning”. (David Kennedy and his work on focused deterrence is another good example.) In the mid 90s when Larry or David did experiments, they likely were directly involved in a way that I am suggesting – the departments are going and asking Larry “what should we do”.

My personal experience, trying to apply many of the lessons of David’s and Larry’s work (which was started around 30 years ago at this point), is not quite like that. It is more of police departments have already committed to doing something (like hotspots), and want help implementing the project, and maybe some grant helps fund the research. Which is hard and important work, but honestly just looks like effective project management (and departments should just invest in researchers/project managers directly, the external funding model does not make sense long term). For a more on point example of what I mean by doing, see what Rob Guerette did as an embedded criminologist with Miami PD.

Part of the reason I wrote the post, if you think about the progression of policing, we have phases – August Vollmer for professionalization in the early 1900’s. I think you could say folks like Larry and David (and Bill Bratton) brought about a new age of metrics to PDs in the 90s.

There are also technology changes that fundamentally impact PDs. Cars + 911 is one. The most recent one is a new type of oversight via body worn cameras. Folks who are leading this wave of professionalization changes are tech folks (like Rick Smith and Anthony Tassone). I think it is a mistake to just sit on the sidelines and see what these folks come up with – I want academic criminologists to be directly involved in the nitty gritty of the implementations of these systems and making them better.

A second response to this is that building stuff is hard, which I agree and did not mean to imply it was as easy as writing papers (it is not). Here is Anthony Tassone’s response on X:

I know this is hard. This is part of why I mentioned the Bell labs path. Working directly for an already established company is much easier/safer than doing your own startup. Bootstrapping a startup is additionally much different than doing VC go big or go home – which academics on sabbaticals and as a side hustle are potentially in a good position to do this.

Laura Huey did this path, and does not have nice things to say about it:

I have not talked to Laura specifically about this, but I suspect it is her experience running the Canadian Society of Evidence Based Policing. Which I would not suggest starting a non-profit either honestly. Even if you start a for-profit, there is no guarantee you will be in a good position in your current academic position to be well supported.

Again no doubt building useful stuff is harder than writing papers. For a counter to these though, doing my bootstrapped consulting firm is definitely not as stressful as building a large company like Anthony. And working for a tech company directly was a good career move for me (although now I spend most of my day building stuff to limit fraud-waste-abuse in Medicaid claims, not improving policing).

My suggestion that the field should be more focused on building stuff was not because it was easier, it was because if you don’t there is a good chance you are mostly irrelevant.

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by apwheele on June 12, 2025  •  Permalink
Posted in Crime Analysis, Criminal Justice, data science, Python, scholarly
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Posted by apwheele on June 12, 2025

https://andrewpwheeler.com/2025/06/12/build-stuff/

LinkedIn is the best social media site

The end goals I want for a social media site are:

  • promote my work
  • see other peoples work

Social media for other people may have other uses. I do comment and have minor interactions on the social media sites, but I do not use them primarily for that. So my context is more business oriented (I do not have Facebook, and have not considered it). I participate some on Reddit as well, but that is pretty sparingly.

LinkedIn is the best for both relative to X and BlueSky currently. So I encourage folks with my same interests to migrate to LinkedIn.

LinkedIn

So I started Crime De-Coder around 2 years ago. I first created a website, and then second started a LinkedIn page.

When I first created the business page, I invited most of my criminal justice contacts to follow the page. I had maybe 500 followers just based on that first wave of invites. At first I posted once or twice a week, and it was very steady growth, and grew to over 1500 followers in maybe just a month or two.

Now, LinkedIn has a reputation for more spammy lifecoach self promotion (for lack of a better description). I intentionally try to post somewhat technical material, but keep it brief and understandable. It is mostly things I am working on that I think will be of interest to crime analysts or the general academic community. Here is one of my recent posts on structured outputs:

Current follower count on LinkedIn for my business page (which in retrospect may have been a mistake, I think they promote business pages less than personal pages), is 3230, and I have fairly consistent growth of a few new followers per day.

I first started posting once a week, and with additional growth expanded to once every other day and at one point once a day. I have cut back recently (mostly just due to time). I did get more engagement, around 1000+ views per day when I was posting every day.

Probably the most important part though of advertising Crime De-Coder is the types of views I am getting. My followers are not just academic colleagues I was previously friends with, it is a decent outside my first degree network of police officers and other non-profit related folks. I have landed several contracts where I know those individuals reached out to me based on my LinkedIn posting. It could be higher, as my personal Crime De-Coder website ranks very poorly on Bing search, but my LinkedIn posts come up fairly high.

When I was first on Twitter I did have a few academic collaborations that I am not sure would have happened without it (a paper with Manne Gerell, and a paper with Gio Circo, although I had met Gio in real life before that). I do not remember getting any actual consulting work though.

I mentioned it is not only better for me for advertising my work, but also consuming other material. I did a quick experiment, just opened the home page and scrolled the first 3 non-advertisement posts on LinkedIn, X, and BlueSky. For LinkedIn

This is likely a person I do not want anything to do with, but their comment I agree with. Whenever I use Service Now at my day job I want to rage quit (just send a Teams chat or email and be done with it, LLMs can do smarter routing anymore). The next two are people are I am directly connected with. Some snark by Nick Selby (which I can understand the sentiment, albeit disagree with, I will not bother to comment though). And something posted by Mindy Duong I likely would be interested in:

Then another advert, and then a post by Chief Patterson of Raleigh, whom I am not directly connected with, but was liked by Tamara Herold and Jamie Vaske (whom I am connected with).

So annoying for the adverts, but the suggested (which the feeds are weird now, they are not chronological) are not bad. I would prefer if LinkedIn had a “general” and “my friends” sections, but overall I am happier with the content I see on LinkedIn than I am the other sites.

X & BlueSky

I first created a personal then Twitter account in 2018. Nadine Connell suggested it, and it was nice then. When I first joined I think it was Cory Haberman tweeted and said to follow my work, and I had a few hundred followers that first day. Then over the next two years, just posting blog posts and papers for the most part, I grew to over 1500 followers IIRC. I also consumed quite a bit of content from criminal justice colleagues. It was much more academic focused, but it was a very good source of recent research, CJ relevant news and content.

I then eventually deleted the Twitter account, due to a colleague being upset I liked a tweet. To be clear, the colleague was upset but it wasn’t a very big deal, I just did not want to deal with it.

I started a Crime De-Coder X account last year. I made an account to watch the Trump interview, and just decided to roll with it. I tried really hard to make X work – I posted daily, the same stuff I had been sharing on LinkedIn, just shorter form. After 4 months, I have 139 followers (again, when I joined Twitter in 2018 I had more than that on day 1). And some of those followers are porn accounts or bots. Majority of my posts get <=1 like and 0 reposts. It just hasn’t resulted in getting my work out there the same way in 2018 or on LinkedIn now.

So in terms of sharing work, the more recent X has been a bust. In terms of viewing other work, my X feed is dominated by short form video content (a mimic of TikTok) I don’t really care about. This is after extensively blocking/muting/saying I don’t like a lot of content. I promise I tried really hard to make X work.

So when I open up the Twitter home feed, it is two videos by Musk:

Then a thread by Per-Olof (whom I follow), and then another short video Death App joke:

So I thought this was satire, but clicking that fellows posts I think he may actually be involved in promoting that app. I don’t know, but I don’t want any part of it.

BlueSky I have not been on as long, but given how easy it was to get started on Twitter and X, I am not going to worry about posting so much. I have 43 followers, and posts similar to X have basically been zero interaction for the most part. The content feed is different than X, but is still not something I care that much about.

We have Jeff Asher and his football takes:

I am connected with Jeff on LinkedIn, in which he only posts his technical material. So if you want to hear Jeff’s takes on football and UT-Austin stuff then go ahead and follow him on BlueSky. Then we have a promotional post by a psychologist (this person I likely would be interested in following his work, this particular post though is not very interesting). And a not funny Onion like post?

Then Gavin Hales, whom I follow, and typically shares good content. And another post I leave with no comment.

My BlueSky feed is mostly dominated by folks in the UK currently. It could be good, but it currently just does not have the uptake to make it worth it like I had with Twitter in 2018. It may be the case given my different goals, to advertise my consulting business, Twitter in 2018 would not be good either though.

So for folks who subscribe to this blog, I highly suggest to give LinkedIn a try for your social media consumption and sharing.

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by apwheele on February 20, 2025  •  Permalink
Posted in data science, Personal Productivity, scholarly, social networking, writing
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Posted by apwheele on February 20, 2025

https://andrewpwheeler.com/2025/02/20/linkedin-is-the-best-social-media-site/

How much do students pay for textbooks at GSU?

Given I am a big proponent of open data, replicable scientific results, and open access publishing, I struck up a friendship with Scott Jacques at Georgia State University. One of the projects we pursued was a pretty simple, but could potentially save students a ton of money. If you have checked out your universities online library system recently, you may have noticed they have digital books (mostly from academic presses) that you can just read. No limits like the local library, they are just available to all students.

So the idea Scott had was identify books students are paying for, and then see if the library can negotiate with the publisher to have it for all students. This shifts the cost from the student to the university, but the licensing fees for the books are not that large (think less than $1000). This can save money especially if it is a class with many students, so say a $30 book with 100 students, that is $3000 students are ponying up in toto.

To do this we would need course enrollments and the books they are having students buy. Of course, this is data that does exist, but I knew going in that it was just not going to happen that someone just nicely gave us a spreadsheet of data. So I set about to scrape the data, you can see that work on Github if you care too.

The github repo in the data folder has fall 2024 and spring 2025 Excel spreadsheets if you want to see the data. I also have a filterable dashboard on my crime de-coder site.

You can filter for specific colleges, look up individual books, etc. (This is a preliminary dashboard that has a few kinks, if you get too sick of the filtering acting wonky I would suggest just downloading the Excel spreadsheets.)

One of the aspects though of doing this analysis, the types of academic publishers me and Scott set out to identify are pretty small fish. The largest happen to be Academic textbook publishers (like Pearson and McGraw Hill). The biggest, coming in at over $300,000 students spend on in a year is a Pearson text on Algebra.

You may wonder why so many students are buying an algebra book. It is assigned across the Pre-calculus courses. GSU is a predominantly low income serving institution, with the majority of students on Pell grants. Those students at least will get their textbooks reimbursed via the Pell grants (at least before the grant money runs out).

Being a former professor, these course bundles in my area (criminal justice) were comically poor quality. I accede the math ones could be higher quality, I have not purchased this one specifically, but this offers two solutions. One, Universities should directly contract with Pearson to buy licensing for the materials at a discount. The bookstore prices are often slightly higher than just buying from other sources (Pearson or Amazon) directly. (Students on Pell Grants need to buy from the bookstore though to be reimbursed.)

A second option is simply to pay someone to create open access materials to swap out. Universities often have an option for taking a sabbatical to write a text book. I am pretty sure GSU could throw 30k at an adjunct and they would write just as high (if not higher) quality material. For basic material like that, the current LLM tools could help speed the process by quite a bit.

For these types of textbooks, professors use them because they are convenient, so if a lower cost option were available that met the same needs, I am pretty sure you could convince the math department to have those materials as the standard. If we go to page two of the dashboard though, we see some new types of books pop up:

You may wonder, what is Conley Smith Publishing? It happens to be an idiosyncratic self publishing platform. Look, I have a self published book as well, but having 800 business students a semester buy your self published $100 using excel book, that is just a racket. And it is a racket that when I give that example to friends almost everyone has experienced in their college career.

There is no solution to the latter professors ripping off their students. It is not illegal as far as I’m aware. I am just guessing at the margins, that business prof is maybe making $30k bonus a semester forcing their students to buy their textbook. Unlike the academic textbook scenario, this individual will not swap out with materials, even if the alternative materials are higher quality.

To solve the issue will take senior administration in universities caring that professors are gouging their (mostly low income) students and put a stop to it.

This is not a unique problem to GSU, this is a problem at all universities. Universities could aim to make low/no-cost, and use that as advertisement. This should be particularly effective advertisement for low income serving universities.

If you are interested in a similar analysis for your own university, feel free to get in touch with either myself or Scott. We would like to expand our cost saving projects beyond GSU.

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by apwheele on February 6, 2025  •  Permalink
Posted in data science, scholarly
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Posted by apwheele on February 6, 2025

https://andrewpwheeler.com/2025/02/06/how-much-do-students-pay-for-textbooks-at-gsu/

The story of my dissertation

My dissertation is freely available to read on my website (Wheeler, 2015). I still open up my hardcover I purchased every now and then. No one cites it, because no one reads dissertations, but it is easily the work I am the most proud of.

Most of the articles I write there is some motivating story behind the work you would never know about just from reading the words. I think this is important, as the story often is tied to some more fundamental problem, which solving specific problems is the main way we make progress in science. The stifling way that academics write peer reviewed papers currently doesn’t allow that extra narrative in.

For example, my first article (and what ended up being my masters thesis, Albany at that time you could go directly into PhD from undergrad and get your masters on the way), was an article about the journey to crime after people move (Wheeler, 2012). The story behind that paper was, while working at the Finn Institute, Syracuse PD was interested in targeted enforcement of chronic offenders, many of whom drive around without licenses. I thought, why not look at the journey to crime to see where they are likely driving. When I did that analysis, I noticed a few hundred chronic offenders had something like a 5 fold number of home addresses in the sample. (If you are still wanting to know where they drive, they drive everywhere, chronic offenders have very wide spatial footprints.)

Part of the motivation behind that paper was if people move all the time, how can their home matter? They don’t really have a home. This is a good segue into the motivation of the dissertation.

More of my academic reading at that point had been on macro and neighborhood influences on crime. (Forgive me, as I am likely to get some of the timing wrong in my memory, but this writing is as best as I remember it.) I had a class with Colin Loftin that I do not remember the name of, but discussed things like the southern culture of violence, Rob Sampson’s work on neighborhoods and crime, and likely other macro work I cannot remember. Sampson’s work in Chicago made the biggest impression on me. I have a scanned copy of Shaw & McKay’s Juvenile Delinquency (2nd edition). I also took a spatial statistics class with Glenn Deane in the sociology department, and the major focus of the course was on areal units.

When thinking about the dissertation topic, the only advice I remember receiving was about scope. Shawn Bushway at one point told me about a stapler thesis (three independent papers bundled into a single dissertation). I just wanted something big, something important. I intentionally sought out to try to answer some more fundamental question.

So I had the first inkling of “how can neighborhoods matter if people don’t consistently live in the same neighborhood”? The second was that my work at the Finn Institute working with police departments, hot spots were the only thing any police department cared about. It is not uncommon even now for an academic to fit a spatial model at the neighborhood level to crime and demographics, and have a throwaway paragraph in the discussion about how it would help police better allocate resources. It is comically absurd – you can just count up crimes at addresses or street segments and rank them and that will be a much more accurate and precise system (no demographics needed).

So I wanted to do work on micro level units of analysis. But I had on my dissertation Glenn and Colin – people very interested in macro and some neighborhood level processes. So I would need to justify looking at small units of analysis. Reading the literature, Weisburd and Sherman did not have to me clearly articulated reasons to be interested in micro places, beyond just utility for police. Sherman had the paper counting up crimes at addresses (Sherman et al., 1989), and none of Weisburd’s work had to me any clear causal reasoning to look at micro places to explain crime.

To be clear wanting to look at small units as the only guidepost in choosing a topic is a terrible place to start. You should start from a more specific, articulable problem you wish to solve. (If others pursuing Phds are reading.) But I did not have that level of clarity in my thinking at the time.

So I set out to articulate a reason why we would be interested to look at micro level areas that I thought would satisfy Glenn and Colin. I started out thinking about doing a simulation study, similar to what Stan Openshaw did (1984) that was motivated by Robinson’s (1950) ecological fallacy. While doing that I realized there was no point in doing the simulation, you could figure it out all in closed form (as have others before me). So I proved that random spatial aggregation would not result in the ecological fallacy, but aggregating nearby spatial areas would, assuming there is a spatial covariance between nearby areas. I thought at the time it was a novel proof – it was not (Footnote 1 on page 9 were all things I read after this). Even now the Wikipedia page on the ecological fallacy has an unsourced overview of the issue, that cross-spatial correlations make the micro and macro equations not equal.

This in and of itself is not interesting, but in the process did clearly articulate to me why you want to look at micro units. The example I like to give is as follows – imagine you have a bar you think causes crime. The bar can cause crime inside the bar, as well as the bar diffusing risk into the nearby area. Think people getting in fights in the bar, vs people being robbed walking away from a night of drinking. If you aggregate to large units of analysis, you cannot distinguish between “inside bar crime” vs “outside bar crime”. So that is a clear causal reasoning for when you want to look at particular units of analysis – the ability to estimate diffusion/displacement effects are highly dependent on the spatial unit of analysis. If you have an intervention that is “make the bar hire better security” (ala John Eck’s work) that should likely not have any impact outside the bar, only inside the bar. So local vs diffusion effects are not entirely academic, they can have specific real world implications.

This logic does not explicitly always value smaller spatial units of analysis though. Another example I liked to give is say you are evaluating a city wide gun buy back. You could look at more micro areas than the entire city, e.g. see if it decreased in neighborhood A and increased in neighborhood B, but it likely does not invalidate the macro city wide analysis. Which is just an aggregate estimate over the entire city – which in some cases is preferable.

Glenn Deane at some point told me that I am a reductionist, which was the first time I heard that word, but it did encapsulate my thinking. You could always go smaller, there is no atom to stop at. But often it just doesn’t matter – you could examine the differences in crime between the front stoop and the back porch, but there is not likely meaningful causal reasons to do so. This logic works for temporal aggregation and aggregating different crime types as well.

I would need to reread Great American city, but I did not take this to be necessarily contradictory to Sampson’s work on neighborhood processes. Rob came to SUNY Albany to give a talk at the sociology department (I don’t remember the year). Glenn invited me to whatever they were doing after the talk, and being a hillbilly I said I need to go back to work at DCJS, I am on my lunch break. (To be clear, no one at DCJS would have cared.) I am sure I would have not been able to articulate anything of importance to him, but I do wish I had taken that opportunity in retrospect.

So with the knowledge of how aggregation bias occurs in hand, I had formulated a few different empirical research projects. One was the idea behind bars and crime I have already given an example of. I had a few interesting findings, one of which is that diffusion effects are larger than the local effects. I also estimated the bias of bars selecting into high crime areas via a non-equivalent dependent variable design – the only time I have used a DAG in any of my work.

I gave a job talk at Florida State before the dissertation was finished. I had this idea in the hotel room the night before my talk. It was a terrible idea to add it to my talk, and I did not prepare what I was going to say sufficiently, so it came out like a jumbled mess. I am not sure whether I would want to remember or forget that series of events (which include me asking Ted Chiricos if you can fish in the Gulf of Mexico at dinner, I feel I am OK in one-on-one chats, group dinners I am more awkward than you can possibly imagine). It also included nice discussions though, Dan Mear’s asked me a question about emergent macro phenomenon that I did not have a good answer to at the time, but now I would say simple causal processes having emergent phenomenon is a reason to look at micro, not the macro. Eric Stewart asked me if there is any reason to look at neighborhood and I said no at the time, but I should have said my example gun buy back analogy.

The second empirical study I took from broken windows theory (Kelling & Wilson, 1982). So the majority of social science theories some spatial diffusion is to be expected. Broken windows theory though had a very clear spatial hypothesis – you need to see disorder for it to impact your behavior. So you do not expect spatial diffusion, beyond someones line of site, to occur. To measure disorder, I used 311 calls (I had this idea before I read Dan O’Brien’s work, see my prospectus, but Dan published his work on the topic shortly thereafter, O’Brien et al. 2015).

I confirmed this to be the case, conditional on controlling for neighborhood effects. I also discuss how if the underlying process is smooth, using discrete neighborhood boundaries can result in negative spatial autocorrelation, which I show some evidence of as well.

This suggests that using a smooth measure of neighborhoods, like Hipp’s idea of egohoods (Hipp et al., 2013), I think is probably more reasonable than discrete neighborhood boundaries (which are often quite arbitrary).

While I ended up publishing those two empirical applications (Wheeler, 2018; 2019), which was hard, I was too defeated to even worry about posting a more specific paper on the aggregation idea. (I think I submitted this paper to Criminology, but it was not well received.) I was partially burned out from the bars and crime paper, which went at least one R&R at Criminology and was still rejected. And then I went through four rejections for the 311 paper. I had at that point multiple other papers that took years to publish. It is a slog and degrading to be rejected so much.

But that is really my only substantive contribution to theoretical criminology in any guise. After the dissertation, I just focused on either policy work or engineering/method applications. Which are much easier to publish.

References

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by apwheele on January 15, 2025  •  Permalink
Posted in Crime Analysis, Crime Mapping, Criminal Justice, scholarly, writing
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Posted by apwheele on January 15, 2025

https://andrewpwheeler.com/2025/01/15/the-story-of-my-dissertation/

Some things work

A lawyer and economist Megan Stevenson last year released an essay that was essentially “Nothing Works” 2.0. For those non-criminologists, “nothing works” was a report by Robert Martinson in the 1970’s that was critical of the literature on prisoner rehabilitation, and said to date that essentially all attempts at rehabilitation were ineffective.

Martinson was justified. With the benefit of hindsight, most of the studies Martinson critiques were poorly run (in terms of randomization, they almost all were observational self selected into treatment) and had very low statistical power to detect any benefits. (For people based experiments in CJ, think you typically need 1000+ participants, not a few dozen.)

Field experiments are hard and messy, and typically we are talking about “reducing crime by 20%” or “reducing recidivism by 10%” – they are not miracles. You can only actually know if they work using more rigorous designs that were not used at that point in social sciences.

Stevenson does not deny those minor benefits exist, but moves the goalposts to say CJ experiments to date have failed because they do not generate wide spread sweeping change in CJ systems. This is an impossible standard, and is an example of the perfect being the enemy of the good fallacy.

A recent piece by Brandon del Pozo and colleagues critiques Stevenson, which I agree with the majority of what Brandon says. Stevenson’s main critique are not actually with experiments, but more broadly organizational change (which del Pozo is doing various work in now).

Stevenson’s critique is broader than just policing, but I actually would argue that the proactive policing ideals of hotspots and focused deterrence have diffused into the field broadly enough that her points about systematic change are false (at least in those two examples). Those started out as individual projects though, and only diffused through repeated application in a slow process.

As I get older, am I actually more of the engineer mindset that Stevenson is critical of. As a single person, I cannot change the whole world. As a police officer or crime analyst or professor, you cannot change the larger organization you are a part of. You can however do one good thing at a time.

Even if that singular good thing you did is fleeting, it does not make it in vain.

References

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by apwheele on October 6, 2024  •  Permalink
Posted in Crime Analysis, Criminal Justice, scholarly
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Posted by apwheele on October 6, 2024

https://andrewpwheeler.com/2024/10/06/some-things-work/

GenAI is not a serious solution to California’s homeless problem

This is a rejected op-ed (or at least none of the major papers in California I sent it to bothered to respond and say no-thanks, it could be none of them even looked at it). Might as well post it on personal blog and have a few hundred folks read it.

Recently Gov. Newsom released a letter of interest (LOI) for different tech companies to propose how the state could use GenAI (generative artificial intelligence) to help with California’s homeless problem. The rise in homelessness is a major concern, not only for Californian’s but individuals across the US. That said, the proposal is superficial and likely to be a waste of time.

A simple description of GenAI, for those not aware, are tools to ask the machine questions in text and get a response. So you can ask ChatGPT (a currently popular GenAI tool) something like “how can I write a python function to add two numbers together” and it will dutifully respond with computer code (python is a computer programming language) that answers your question.

As someone who writes code for a living, this is useful, but not magic. Think of it more akin to auto-complete on your phone than something truly intelligent. The stated goals of Newsom’s LOI are either mostly trivial without the help of GenAI, or are hopeless and could never be addressed with GenAI.

For the first stated goal, “connecting people to treatment by better identifying available shelter and treatment beds, with GenAI solutions for a portable tool that the local jurisdictions can use for real-time access to treatment and shelter bed availability”. This is simply describing a database — one could mandate state funded treatment providers to provide this information on a daily basis. The technology infrastructure to accomplish this is not much more complex than making a website. Mandating treatment providers report that information accurately and on a timely basis is the hardest part.

For the second stated goal, “Creating housing with more data and accountability by creating clearer insights into local permitting and development decisions”. Permitting decisions are dictated by the state as well as local ordinances. GenAI solutions will not uncover any suggested solution that most Californian’s don’t already know — housing is too expensive and not enough is being built. This is in part due to the regulatory structure, as well as local zoning opposition for particular projects. GenAI cannot change the state laws.

For the last stated goal of the program, “Supporting the state budget by helping state budget analysts with faster and more efficient policy”. Helping analysts generate results faster is potentially something GenAI can help with, more efficient policy is not. I do not doubt the state analysts can use GenAI solutions to help them write code (the same as I do now). But getting that budget analysis one day quicker will not solve any substantive homeless problem.

I hate to be the bearer of bad news, but there are no easy answers to solve California’s homeless crisis. If a machine could spit out trivial solutions to solve homelessness in a text message, like the Wizard of Oz gifting the Scarecrow brains, it would not be a problem to begin with.

Instead of asking for ambiguous GenAI solutions, the state would be better off thinking more seriously about how they can accomplish those specific tasks mentioned in the LOI. If California actually wants to make a database of treatment availability, that is something they could do right now with their own internal capacity.

Solutions to homelessness are not going to miraculously spew from a GenAI oracle, they are going to come from real people accomplishing specific goals.

If folks are reading this, check out my personal consulting firm, Crime De-Coder. I have experience building real applications. Most of the AI stuff on the market now is pure snake oil, so better to articulate what you specifically want and see if someone can help build that.

Crime De-Coder consulting

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by apwheele on September 30, 2024  •  Permalink
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Posted by apwheele on September 30, 2024

https://andrewpwheeler.com/2024/09/30/genai-is-not-a-serious-solution-to-californias-homeless-problem/

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