One of the things I keep thinking about is @justinamash's bill to end Qualified Immunity. It's not a perfect solution + I don't think it goes nearly far enough, but it's a concrete policy that has merit + can have a positive impact for thousands who have been denied justice.
Obviously, no one *really* likes tort law, but it's an interesting vehicle that may be able to change incentive structures + drive (much needed) reform to policing (especially at the local level).
Removing QI opens the door for a host of legal remedies (discovery, civil suits, criminal charges), as well as removes a significant bargaining chip that pushes victims of police brutality toward a settlement vs. a day in court.
Right now, most cities have a line item for settling police lawsuits. It's just "the cost of doing business" -- which is why things don't change. But if that cost of doing business increased 100x overnight, it probably would. That penny on the dollar becomes the whole dollar.
Next, personal "malpractice" insurance should be mandatory for every officer - just as it is for every attorney, every doctor + every person who operates a motor vehicle. If you can't be insured, then you can't be a cop. This adds another layer of accountability + oversight.
Buit again, this might not be enough. So we need a national registry for all police officers, which includes all of their badge numbers, record of service, complaints + insurance provider. And as with the Bar association, complaints must be handled by an independent investigator.
This removes the defense from municipalities that they "didn't know" about an officers misconduct + significantly lowers the probability that such misconduct will be papered over -- because again, independent investigator AND private, third-party insurance.
In order to make hiring bad cops *even more* expensive for cities/PDs, remove all punitive damage caps on instances of police brutality, overreach, rights violations, assault, etc. Then (as happened with the Catholic Church) provide a look-back window where the SoL is waived.
There will be some eye-popping verdicts, which will scare the bejesus out of police departments everywhere...especially if police pension funds are fair game for settlements (which they absolutely should be). Now good cops are incented to remove bad cops.
Because one bad cop doing something dumb or thug-ish could mean a (significant) hit to the good cop's pension + retirement security. That'll put the #BlueWallOfSilence to the test. Again, boring + definitely not sexy. But sometimes you've got to break systems by a thousand cuts.
In addition to all that, I do think every mayor should sign a "One Strike" policy for officers: one instance of brutality or abuse = immediate removal from the force, immediate cessation of pay, no reinstatement anywhere for 2 years (why the national registry is critical).
One thing I think would come out of this: significantly better candidate recruitment + training (esp. in de-escalation) -- not only will PDs see that better-trained officers are much less likely to engage in unnecessary violence, but they are able to achieve better outcomes.
Obviously the @GLFOP will hate *all* of this, but that's usually a good sign that we're on the right track. This is by no means exhaustive, but I think this has a decent shot of *starting* to correct the flaws in the system. I firmly believe incentives - financial + legal - work.
I get that a lot of people are hurting + angry right now - but I do think we need to come up with concrete policy proposals focused on correcting systematic injustice - and that starts with re-aligning incentives + removing barriers to justice.
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There's a lot of discourse on here (and on LI) about AI companies "stealing" copyrighted materials for training.
There are - fundamentally - two different issues at play. The fact that most conversations conflate them creates more problems.
The first issue is the use of publicly- available data to train models.
The second (and more serious) is companies using LLMs to unbundle content from creators (people, businesses, organizations, whatever) in a way that could cause real harm.
Issue #1: Training Data -- LLMs are trained on vast amounts of data, ranging from patent filings and old novels to newspaper articles, blogs, reviews, forum content, encyclopedias, etc.
This content is used by the LLM to generate patterns.
There's a lot of commotion, confusion and fear about Google's removal of 3P cookies + what that means for advertisers.
Much of this is unwarranted and ridiculous:
First, there's a misconception that the removal of 3P cookies from chrome somehow impacts Google's data (1P cookies) - nope.
This will impact many third-party services, from smaller (relative to Google/Meta/Apple) ad platforms, to attribution platforms, to certain UI/UX platforms, to other website service providers (basically - any third party that uses a pixel/tracking tag).
Whenever major changes occur, there are winners & losers.
I view this as an overwhelming positive for Meta, Google, Amazon & Apple.
It is an overwhelming positive for marketers.
It is likely a massive win for most users, who will get better, faster, cleaner web and ad experiences.
It is a massive negative for parasitic data leeches, along with the brands that rely on their less-than-optimal 3P data for marketing, to the exclusion of building 0P/1P audiences.
It is a massive negative for publishers + brands who have not invested in building their 0P/1P data capabilities.
Just spent some time playing around with the Google Demand Gen Beta. Initial reactions & takeaways:
1. RIP Discovery - I've long been a big fan of discovery campaigns, though DG appears to be a level-up from existing Discovery for 4 reasons:
(1) Inclusion of YT placements (2) ML-driven targeting options (similar to Meta) (3) Ability to create LALs (4) Standard Bidding Strats
2. Lookalike Segments - I love a good Lookalike. Done well, it jump-starts machine learning + helps reduce wasted/unproductive spend. This is a HUGE benefit to organizations that have invested in their zero-party data infrastructure.
Google Ads is an area where brands invest heavily, all with little-to-no transparency on what that investment is returning. I've done 100+ audits covering hundreds of millions in spend - and here are the 10 things that result in suboptimal outcomes (+ lots of wasted $$$)👇
"Let's break this down into five core buckets -
1. Strategy & Research 2. Account & Campaign Structure 3. Data Flows 4. Creative & Landers 5. Management
High performance in each of these areas is *essential* if your goal is to build + maintain a highly profitable account."
Strategy & Research
In roughly ~90% of audits, the biggest failures are NOT a result of tactical mistakes; they are a result of strategic failures. Just as a house built on a crappy foundation will fail, so too will a Google Ads account built on a flawed strategy
So #MarketingTwitter you've heard about the big scary antitrust case against Google that was brought by a bunch of states you wouldn't expect to be suing big business (TX, KY, AK, ID, IN, MI, MS, ND, SD, UT) + wondering what's it all about, here are some (preliminary) thoughts:
(Disclaimer: I have no idea how long this thread is going to go so :shrug: and stop reading whenever you get bored)
2/x
From a high-level, the case is primarily focused on a vulnerability for Google (AdX), with some (IMO) stupid digressions around search market share and an illicit agreement with Facebook to cripple header bidding. In that sense, it's a case that has some merit.
3/x
@NeptuneMoon I don't know if I'm an "expert" -- but as someone who worked in finance + now does lots of digital things, this is a really, really dumb take, for (at least) 5-6 reasons:
Thread time, because I want to procrastinate and way too many people don't understand how MBS or ABS work.
@NeptuneMoon Reason #1 - MBS issues resulted in a systemic failure due to a heinous combination of securitatization, proliferation of CDOs, deregulation, fraud + general stupidity (simplified).
The *combination* is what allowed the situation to go from an isolated bad to a global really bad.
@NeptuneMoon As I understand it, Hwang's argument is (basically): 1. online advertising doesn't deliver the value it claims 2. but people keep buying it, so prices keep going up 3. lots of companies rely on it for $$$ 4. so if people figure out (1) + stop (2), then BOOM.