Smaller departments that struggle with the cost of equipment and storage of data are ending or suspending programs aimed at transparency and accountability.
Original question on Quora: Why does the Harvard Business School, Michael Porter, teach the essence of business strategy is the elimination of competition, by regulation if possible. Is this legal? Is this basically socialism or communism?
My response: Trying to pin this on Michael Porter is ridiculous. He says no such thing. Based on the way the question is phrased, I wonder if there is an ideological purpose in asking it.
But in any case, there is a serious issue behind the question, namely an increasing level of oligopoly (decreasing levels of competition) among companies in many US industries. See, for example, “Big Companies Are Getting a Chokehold on the Economy Even Goldman Sachs is worried that they’re stifling competition, holding down wages and weighing on growth.” or.
“America Has a Monopoly Problem—and It’s Huge”.
One theory about this trend is that it is partly due to growing power of corporations in Washington. That, in turn, may be traced partly to the increasing role of money in elections, largely as a result of the infamous Supreme Court “Citizens United” decision. For example, the way Trump’s massive tax cuts were put together without any hearings and in a VERY short period of time, and the amount of “goodies” for many industries in the resulting package, would never have happened with previous massive changes in taxes.
An effective strategy in some highly concentrated industries is to persuade the government to selectively regulate your industry, in ways that favor large and established companies. That is, all companies may experience higher costs because of a regulation, but if your company can respond more cheaply than anyone else, it is still a net win for you. An example is pharmaceuticals. For example pharma companies increasingly use the legal system, regulations, and side deals to keep generic drugs off the market for years after drug patents expire. The industry has also been very effective at keeping foreign competitors out – e.g. blocking imports by individual citizens from Canada.
(I buy one medication at $1 per pill from abroad, when it costs $30/pill at the local Rite-Aid. But it takes a lot of research and effort.)
Source: (32) Why does the Harvard Business School, Michael Porter, teach the essence of business strategy is the elimination of competition, by regulation if possible. Is this legal? Is this basically socialism or communism? – Quora
Here is an argument for allowing companies to maintain a lot of secrecy about how their data mining (AI) models work. The claime is that revealing information will put companies at a competitive disadvantage. Sorry, that is not enough of a reason. And it’s not actually true, as far as I can tell.
The first consideration when discussing transparency in AI should be data, the fuel that powers the algorithms. Because data is the foundation for all AI, it is valid to want to know where the data…
Here is my response.
Your questions are good ones. But you seem to think that explainability cannot be achieved except by giving away all the work that led to the AI system. That is a straw man. Take deep systems, for example. The IP includes:
1) The training set of data
2) The core architecture of the network (number of layers etc)
3) The training procedures over time, including all the testing and tuning that went on.
4) The resulting system (weights, filters, transforms, etc).
5) HIgher-level “explanations,” whatever those may be. (For me, these might be a reduced-form model that is approximately linear, and can be interpreted.)
Revealing even #4 would be somewhat useful to competitors, but not decisive. The original developers will be able to update and refine their model, while people with only #4 will not. The same for any of the other elements.
I suspect the main fear about revealing this, at least among for-profit companies, is that it opens them up to second-guessing . For example, what do you want to bet that the systems now being used to suggest recidivism have bugs? Someone with enough expertise and $ might be able to make intelligent guesses about bugs, although I don’t see how they could prove them.
Sure, such criticism would make companies more cautious, and cost them money. And big companies might be better able to hide behind layers of lawyers and obfuscation. But those hypothetical problems are quite a distance in the future. Society deserves to, and should, do more to figure out where these systems have problems. Let’s allow some experiments, and even some different laws in different jurisdictions, to go forward for a few years. To prevent this is just trusting the self-appointed experts to do what is in everyone else’s best interests. We know that works poorly!
There is a lot of concern about AI potentially causing massive unemployment. The question of whether “this time will be different” is still open. But another insidious effect is gaining speed: putting tools in the hands of large companies that make it more expensive and more oppressive to run into financial trouble. In essence, harder to live on the edges of “The System.”
- Cars with even one late payment can be spotted, and repossessed, faster. “Business has more than doubled since 2014….” This is during a period of ostensible economic growth.
- “Even with the rising deployment of remote engine cutoffs and GPS locators in cars, repo agencies remain dominant. … Agents are finding repos they never would have a few years ago.”
- “So much of America is just a heartbeat away from a repossession — even good people, decent people who aren’t deadbeats,” said Patrick Altes, a veteran agent in Daytona Beach, Fla. “It seems like a different environment than it’s ever been.”
- “The company’s goal is to capture every plate in Ohio and use that information to reveal patterns. A plate shot outside an apartment at 5 a.m. tells you that’s probably where the driver spends the night, no matter their listed home address. So when a repo order comes in for a car, the agent already knows where to look.”
- Source: The surprising return of the repo man – The Washington Post
My friend Don Norman wrote an op-ed this weekend calling for an FDA-like testing program before autonomous cars are put on the roads in the US. Clearly, some level of government approval is important. But I see lots of problems with using drug testing (FDA = Food and Drug Administration) as a model.
Here is an excerpt from a recent article about testing problems with Uber cars, which were the ones in the recent fatal accident. After the break, my assessment of how to test such cars before they are allowed on American roads.
Waymo, formerly the self-driving car project of Google, said that in tests on roads in California last year, its cars went an average of nearly 5,600 miles before the driver had to take control from the computer to steer out of trouble. As of March, Uber was struggling to meet its target of 13 miles per “intervention” in Arizona, according to 100 pages of company documents obtained by The New York Times and two people familiar with the company’s operations in the Phoenix area but not permitted to speak publicly about it.Yet Uber’s test drivers were being asked to do more — going on solo runs when they had worked in pairs.And there also was pressure to live up to a goal to offer a driverless car service by the end of the year and to impress top executives.
So Uber car performance was more than 100 times worse than Waymo cars?!
Academia has a problem: the value, necessity, and practices of collaboration are increasing, but the system of giving credit is inadequate. In most fields, there are only 4 levels of credit:
- None at all
- “Our thanks to Jill for sharing her data.” (a note of thanks)
- First Authorship (This is ambiguous: it may be alphabetical.)
- Listed as another author
In contrast to this paucity, modern empirical paper writing has many roles. Here are a dozen roles. Not all of them are important on a single paper, but each of them is important in some papers.
- Intellectual leadership.
- Source of the original idea
- Doing the writing
- Writing various parts, e.g. literature review
- Doing the grunt work on the stat analysis. (Writing and running the R code)
- Doing the grunt work of finalizing for publication. (Much easier than it used to be!)
- Dealing with revisions, exchanges with editors, etc.
- Source of the data.
- Funder of the data
- Raised the funding;
- Runs the lab where the authors are employed
- Source of the money: usually an agency or foundation, but sometimes the contracting author is listed as a coauthor.
I recently received the following on a Dave Farber’s “Interesting People” list, a collection of techies with interest in Internet policy issues. Why discuss it now, since the tax bill has been passed? It is important for all to realize how much the Republicans in Washington no longer believe in basing their decisions on reality (“facts”). It is very hard to believe this, but the evidence is now overwhelming, and the consequences will continue to be grave. I wrote the following quick response.
It seems completely reasonable and even desirable to take actions such as lowering corp taxes, lowering taxes on productivity and reducing regulation to get the economy growing at the 3-4% range.