An Important Tech Job That Doesn't Exist
alexkrupp.typepad.com
alexkrupp.typepad.com
My start-up vocabulary is failing me here so I'm going to have to use an analogy.
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In boxing, the most profitable fighter is not necessarily the best fighter.
A promoter will use an expert eye for the sound fundamentals of a great fighter at least as much to avoid bad match-ups for his prospects as he will to find those prospects in the first place.
Great fighters are not necessarily marketable fighters and their value falls through the through floor once they take an L.
What the promoter really wants is the right face, a guy with a great story and charisma, someone the people will pay to watch beat up cab drivers - he needs him to be good, but only good enough.
The promoter has all the resources to arrange the rest.
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So, is the issue that the VCs are overlooking / ignorant to these technical factors of great companies or is it simply that great companies are too much effort when they can get rich(er) on status quo games of cash and connections?
If the market is rewarding me-too mobile apps, then by Christ that's what they'll fund, because that's where the money is. Why fund a cancer drug or space company or whatever when there is no clear case that that is going to make a good ROI (or succeed at all).
The perception is that VCs are the money-men behind startups that change the world and make everything better and create value and value. The reality instead is that they have to make money and pay for themselves too, and the surest way to do that is to bet on "safe" products and things the market provably wants.
It is a great shame that the narrative is that VC-backed startups are the best actors for positive progress--I don't think we could be further from the truth.
[1] Sergey's academic homepage: http://infolab.stanford.edu/~sergey/
PS: 3am here so I am probably missing something obvious.
Namely that it is "creator-owned" https://uwaterloo.ca/research/waterloo-commercialization-off...
But I didn't see the article as a complaint that "investors are wrong", but rather "before you spend months inventing and building a new UX flow, take a few days to read about the latest research".
If a developer needs a balanced binary tree, they will first look for an existing implementation in the language they are using. If one doesn't exist, a good developer will check Knuth/CLRS/Wikipedia for the suitable algorithms and build it based on these recommendations, instead of jumping in and hacking something together on the spot.
I think the article argues that UX and product design could use a similar approach. If you are deliberately testing a new approach, sure, go build whatever comes to mind. But if you just need an "incentive mechanism" in your app, then it makes sense to read up about the existing research on what kinds and how large incentives work, instead of making a guess on the spot. And even if you are innovating on some aspect, it's useful to use the existing best practices as the starting point and improve & measure from there.
> Of all the social sciences, the following seem to be disproportionately valuable in terms of creating and evaluating startups:
> Psychology / Social Psychology
> Internet Psychology / Computer Mediated Communication
> Cognitive Development / Early Childhood Education
> Organizational Behavior
> Sociology
> Education Research
> Behavioral Economics
> And yet not only is no one hiring for this, but having expertise in these areas likely won't even get you so much as a nominal bonus.
The core argument of this article -- that designers at top startups are not hired for their CogSci/etc chops -- is patently false in my experience. Has this person gone actually gone and talked with design leads at startups?
Designers just fuxx around in photoshop. Sure.
Psychology is pseudo-science. N = 1 is no way to conduct a serious scientific endeavor.
Internet psychology? lol
Cognitive development / Childhood behavior - Ever hear of COPA? Many developers/designers/projects will never deal with anything front-facing involving anyone under the age of 13.
Organization behavior - hmmmm
Sociolgy - well....
Education Research - I suppose if your project is focusing on training/education you would want to be practicing best pedagogic practices.
Behavioral Economics - Cereally? I don't know how fundamental we need to get into treating our users as "active agents." Can't we just see them as the people they are and still succeed?
To conclude, all I can say is from my experience T=the best designers are born, not honed in the hoary halls of the academy, divorced as they are from the real world.
http://www.economist.com/news/briefing/21588057-scientists-t...
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1182327/
It's a crisis worth becoming aware of and thinking about the implications of.
In contrast with Facebook, one of the reason why
FourSquare has yet to succeed is due to significant
problems with their initial design decisions ...
This doesn't necessarily detract from the bigger argument which is it is useful to know the research relevant in your field.
By analogy... Many hedge funds don't act like they know current financial theory. (Example: Icann) Others (Example: AQR) base their entire existence on being current on research.
On Tumblr 4.5 years ago: https://news.ycombinator.com/item?id=961523
On Twitter from 2007: http://alexkrupp.typepad.com/sensemaking/2007/08/what-makes-...
On Wikipedia from 2004: http://beta.slashdot.org/story/04/09/05/1339219/wikipedia--a... (user pHatidic)
On Squidoo from 2006: http://en.wikipedia.org/wiki/Wikipedia:Articles_for_deletion...
Obviously I wasn't trying to make predictions in these posts, let alone predictions that would look correct ten years later, but I think you'll see that I have a pretty good track record of being on the right side of history way before these sites hit their tipping points and became mainstream. But regardless, it's not really about making predictions, it's about knowing what questions to ask in order to better understand the founders and the marketplace. Ultimately you have to decide who to bet on, but I think it would be a mistake to confuse a bet with a prediction.
Also, after having read a lot of social science research, the research is pretty crap for the most part. I'm sure there are a few gems in there, but you have to read a lot of positive results from badly-thought-out experiments with obvious holes to get to the few nuggets of truth.
Much, much, easier and faster to conduct your own experiment by building something and seeing how customers react to it.
Before something fails, it can be very difficult to notice it, and even more difficult to differentiate it from all the other obvious things that will kill it but actually never will.
It's hard to make predictions, especially about the future.
But... paying someone to make that prediction (even if you largely trust their authority) is not actually helpful.
Behavioral research and drawing insights from huge amounts of social data is definitely useful for the startup industry. But people can do this completely outside of academia where there aren't massive barriers to entry. And they can share their findings using blogs, books, github, consulting, etc.
The University of Central Florida's College of Engineering as entire courses taught by real world professionals from Lockheed, TI, Duke Energy, Boeing, Harris Corp, Orbital, NASA, etc etc etc. They also work very closely with students who are working on unique research projects and connecting them with experienced professionals that can help with the real world side of the research.
I'm sure UCF is not unique, it's just what I'm most familiar with.
Sounds like there's a startup or two in decision support anyhow.
Best practices do not come from academia. Especially not regarding software engineering.
Now let's cover why not. Simply put: academic research often is only tangentially related, and thus of limited value. The people with the most direct expertise in the area in question, are the ones who are actually doing the technology they're developing, on a day to day basis.
Since the article actually specifies behavioral research, I think my background in anthropology and the social sciences might be helpful here. My research for the past ~year has been on the culture of Quantified Self, but I'm also coming from a background of Human-Computer Interaction and I'm going to study HCI at Stanford (sooner or) later this year.
What I generally call "behavioral" research is just too specific to be applicable without an academician him/herself to parse, abstract, and apply this stuff. Worse, you would be hard-pressed to find an anthropologist (or I suspect any other social scientist) who would be able, let alone willing, to make any predictions about the future, even in their own niche. My thesis's discussion section looks at the future of QS culture as it relates to mainstream culture, but I'm not willing to make any predictions at all. The most brazen thing I'm willing to do is highlight some of my observations and follow where those observations might lead. I immediately underscore that these are total unknowns, and that we should all just keenly watch QS culture for how these issues will play out.
That kind of non-committal culture (at least in the social sciences) is favored in academia because it's incredibly difficult to correctly guess or predict the future, especially when humans are the subject of research (and especially when they're aware of the prediction you're making, because they so often seem to want to prove you wrong). You want your research to stand the test of time, and making predictions that don't bear out undercuts your credibility.
So you won't read any journal articles in sociology or anthropology that definitively tell you what you should make your next startup about, and any interpretation between the lines you read will invariably be contentious. For all of my research, I wouldn't bet my lunch on any particular prediction.
Instead, it makes much more sense to have a UI/UX specialist whose job includes knowing the research and academic consensus on stuff. Maybe they should keep their ear to the ground to hear for any trends or new paradigms in user interface design, but whether this person can even shoehorn that stuff into real-world business endeavors is questionable.
All that being said, I think I agree with the idea that a startup should be cognizant of research in the area they're trying to break into. But that sounds (to me, anyway) like I'm advocating that in the process of doing a business plan and analyzing competitors someone should do a cursory search for existing literature on this topic to make sure there are no land mines in the field. If someone wanted to get into medical informatics but had no idea about HIPAA-compliance and the complications that injects, I would steer clear.
It's not actually that it's difficult to predict the future -- it's just as difficult in industry, but they try all the time!
It's that it's difficult to prove in a peer-reviewed article that your prediction is correct. Academics don't try to say anything that can't pass peer-review.
This filter of peer-review is what limits academics from speculating. In industry, you are free of peer-review. Steve Jobs can predict that the world is moving to multi-touch phones, and it doesn't matter if his peers complain that there aren't any buttons or physical keys. He will be proven right in the marketplace.
I would expect predictions, just like a new physical theory or observation may accompany bold predictions following from it's premises.
Never underestimate the challenge in an undertaking like that--or the profits.
Kids are the insiders. They don't need someone to tell them that something fascinating is going on in their own world. It's the only world they've ever known. They don't know of anything else.
The literature is written by the reporters. The kids using the technology are on the battlefield. They don't need a reporter to tell them what's going on.
Not sure about math here. Lets say that average increase is $0.5M and only 1% gets funded. In that case it is around $5,000 per study to break even. I do not think investors could fit reliable evaluation into this money.
This person has never experienced the ridiculously huge different in productivity between startups/small to medium sized organizations and those big inefficient beasts like banks/telcos/government departments.
The sort that gives data and backs its claims up by evidence (empirical, controlled etc.) if possible.
This is what I recently recommended to new employees at my company. The three authors are highly respected researchers in the field. Here is a TED talk by Alison Gopnik (the main author) for a sense of her work on babies' and young children's natural readiness and ability to learn: http://www.ted.com/talks/alison_gopnik_what_do_babies_think
Software culture is, to my surprise, deeply anti-intellectual. Crass commercialism has driven out everything better, and the result is that a discipline (technology) that ought to be focused on improving human life is, instead, focused on helping business assholes unemploy people.
Of course, the cost-cutting anti-intellectual shitbirds don't limit their damage to outside of their companies, so R&D is one of the first things they attack when they need to free up cash for their unreasonable bonuses.