Graduate students are the labor in academic science and engineering

People giving out grants try to derisk them as much as possible

Manufacturing is important and often ignored

The word ‘novel’ is used as an idea bludgeon in academia

All the incentives in research drive towards conservatism

Peer review doesn’t catch duplications

Bell Labs is one of the few examples of an innovation org that was aligned with its money factory

A new professor needs about $1.5m to get going

Academic culture prizes individual recognition

Younger professors have to spend more time getting money

Academics are incentivized to do peer-reviewed publishable work

Things that are not paper-worthy enough for academia and not product-focused enough for a startup

Pay-it-forward tithing could resolve the tension between the potential public-good and potential profit in research.

The idea that academia is for crazy exploration and companies are for low risk exploration is bullshit

Three myths about scientific peer review

A PI needs to provide evidence that they have access to a lab facility

Different axes of where research gets done in the US

What was the real incentive for people to work on the DARPA Grand Challenge?

It is easier to have a multipoint mutation in technology than in evolution

NS Notes on Officers Techniques

Necrobotics illustrates how academia forces engineering

The boundaries between industry government and academia are fuzzy

Startups and Academia are bad at addressing structural constraints

The Architected Innov􏰂ation Institute - Engineering Scientific Revolutions

There are very few senior individual contributors in academia

Is it more impactful to find and train undiscovered diamonds or to unlock well-positioned but constrained researchers?

Wolfgang Merkt conversation 12 Oct 2021

An institution riffing on the ARPA Model could enable paradigm shifts that are not happening

Academic administrators and professors are playing very different games

An Institute for Creative Technology - Riffing on ARPA

Funding structures lead to several layers of indirection on what even gets proposed

Is it possible that we’re actually getting less research because we have more researchers?

Running list of relevant science news?

# §Academia Constraints
- [[Academia is the game where you gain status by getting attention for new knowledge]]

- [[Universities have multiple conflicting missions]]
- [[Universities have been pushed more towards applied research since the end of WWII]]
- [[Academic credit is a first-to-the post system]]
-  [[Graduate students are the labor in academic science and engineering]]
- [[People giving out grants try to derisk them as much as possible]]
- [[Professors do three or more jobs]]
- [[Successful professors are not necessarily the best researchers]]
- [[University professorships are the highest status jobs in academia]]
- [[National labs and other government research centers are a research alternative to universities]]
- [[The game in national labs is roughly the same as academia but with different constraints]]
- [[In academia more grant money leads to more power]]
- [[Academic research is often just the concept half of creating a heuretic]]
- [[Professors are constantly doing the calculation of whether a grant is worth the time to apply for it]]
- [[Most grant money is tagged so unrestricted money is like gold for professors]]
- [[Universities can take more than half of grant money as overhead]]
- [[A PI needs to provide evidence that they have access to a lab facility]]
- [[Physical experiments are expensive]]
- [[Younger professors have to spend more time getting money]]
- [[The government grant process depends on politics and committees]]
- [[Any technology that comes out of a university needs to go through their tech transfer office]]
- [[Months of grant writing is one of the things that makes people think twice about academia]]
- [[Academia incentivizes novelty, not focus]]
- [[Academia is not a good environment for systems engineering]]
- [[Academics are incentivized to do peer-reviewed publishable work]]
- [[Going outside of the approved process can be a black mark against people in academia]]
- [[People proposing work that they have already done is a sign that feedback loops are broken]]
- [[Necrobotics illustrates how academia forces engineering]]
- [[Labs implicitly judge research through the sense of dollars per paper]]

### Related
- [[§Startup Constraints]]
- [[§Corporate R&D Constraints]]
- [[§Philanthropy and Non-Profit Constraints]]
- [[Market Failures in Science]]

[Web URL for this note](http://notes.benjaminreinhardt.com/§Academia_Constraints)

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DARPA does multiple levels of top-down problem generation and bottom-up solution generation

§ARPA model

DARPA PMs use seedling programs to ‘acid test’ the riskiest pieces of a program idea

The DARPA execution framework boils down to showing that thing is not impossible, showing that thing is possible, and then making that thing possible

Program Managers need to be entrepreneurs

Workshops could be a way to start small building a private ARPA

It is hard for a private ARPA to capture value without hamstringing impact

Maverick work is lonely and DARPA provides peers and community

DARPA underutilizes the internet to execute on its model

There are many tight feedback loops built into the ARPA model

Why would people want to work with PARPA?

fuchsRethinkingRoleState2010

How do you have skin in the game around ideas?

One function of a private ARPA is to fill in the gap once filled by corporate R+D

DARPA provides a derisking role for people in other organizations

How to think about the differences between FROs and private ARPA programs

Focused network building is a valuable early step for riffing on ARPA

weaverNSNotesOfficer1946

PARPA needs to be obsessed with PMs

How could the ARPA Model take advantage of the internet?

Wide vs deep networks and Clusters with respect to DARPA

DARPA is a coordination mechanism

The ARPA model can lead to inbreeding

What do online DARPA workshops look like?

Matthew Feldman Conversation 30 Apr 2020

Q2 2021

# A large part of a DARPA program manager’s job is focused network building
 [[fuchsRethinkingRoleState2010]] points out that DARPA program managers act as [‘brokers’ and ‘boundary spanners’ - terms of art for people who connect relatively unconnected clusters of people](https://funginstitute.berkeley.edu/wp-content/uploads/2012/10/Brokerage-2C-Boundary-Spanning-2C-and-Leadership-in-Open-Innovation-Communities.pdf). DARPA PMs network in the literal sense of creating networks, not just plugging into them.  

The idea of *focused* networking is important. DARPA program managers have a clear purpose for building the network - first to generate a clear target in an area, then to solicit paths towards the target, and then to make sure that the people who are executing on those paths know about each other so small adjustments to the plan can happen as frictionlessly as possible.  It is easy to network in an indeterminate way, hoping that the connections you make will be useful one day. This indeterminate approach is how much people go about networking. 

[[“Networking” is just jargon for ‘building relationships with people who aren’t shoved in front of you by life’]] and PMs need to do this at every step of [[The DARPA execution framework boils down to showing that thing is not impossible, showing that thing is possible, and then making that thing possible]].  What does this tactically look like in practice?

In the first step of the process, PMs need to find and become friends with (ideally) everybody who is working on ideas adjacent to the area where they want to have an impact to get a sense of what’s possible. It’s important for PMs to come from the research world so that they already have many of these connections. *Realistically, PMs are able to get this access because they bring the possibility of funding.* PMs also bring these people together in small groups to dig into which possibilities are not impossible and what it would take to make them possible. If the PM is doing their job well the people at the `workshops` won’t already know each other and will continue to poke at ideas together on their own.   The second step of the process leverages the network built during the first step to quickly do seedling programs. [[DARPA PMs use seedling programs to ‘acid test’ the riskiest pieces of a program idea]]. 

During the third step of the process, PMs depend heavily on the network to send unique solutions their way. The PMs host `performer days`  - small private conference for all the people working on different pieces of the program. These conferences force people to talk about the work they’re doing *while* they’re doing it, which while uncomfortable, enables people to share solutions to tricky problems and form more connections. You could imagine this leading to problematic correlation between results because everybody would want to copy whatever the shiniest group is doing but at this point all the performers are locked in to whatever approach they’re trying.

You could think of DARPA PMs as manually playing the role of a [[Designed Serendipity]] system. Both connecting the right people at the right time and giving them an incentive to help each other out. 

[[waldropDreamMachine2018]] talks about how [[JCR Licklider]] was always flying around to different university groups.  In addition to bringing together all the people who thought they were crazy to be interested in human-focused computing, he also helped create several new lab groups.  Today, [[A new professor needs about $1.5m to get going]]. Interestingly, I haven’t seen any organizations devoted to seeding labs in a structured way beyond funding new professors who would have worked on those ideas anyway.

PMs also build networks of people in different classes of organizations - government, academia, startups, and large companies. Connections between different verticals is one way that [[The definition of the ARPA model has changed over time]] -  in 1960’s, large companies had much more academic R&D arms and startups were barely a thing. In this way, DARPA PMs are acting to [[Manage the Transfer not the Technology]].  This shift in the PM role is important. Two reasons that we don’t have more awesome sci fi shit ([[§How do we get more awesome sci-fi shit?]]) that I’ve seen over and over are 1) technology that needs actual manufacturing or high capital investment isn’t able to jump the gap from a lab to a startup prototype or from a startup prototype to a real scalably manufactured product and 2) there are many pieces of technology that are amazing but don’t warrant an entire VC backed startup on their own. It seems like building connections between different organization classes while the technology is being built could address both problems. Worth digging into more. 

In a way, the Program Manager acts like a product manager in a tech company, talking to the customer and modeling their needs. For DARPA the military is the customer but the difference is that the ‘product’ isn’t something that can be purchased (TRL 9) but something that is proved out enough that other branches of the military.

### Related
- [[DARPA facilitates idea sex both between PMs and Performers]]
- [[Definiteness means that you have a long-term plan]]
- [[The ARPA model may be able to utilize the internet for awesome]]
- [[DARPA underutilizes the internet to execute on its model]]



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A large part of a DARPA program manager’s job is focused network building

Trust-building timescale and budgets tend to be similar in different domains

# A new professor needs about $1.5m to get going
# A new professor needs about -1-5m to get going
This money is meant to help set up a lab and buy equipment

According to this list of grants [New Faculty/Young Investigators | FSU Office of Research](https://www.research.fsu.edu/research-offices/ord/finding-funding/new-facultyyoung-investigators/) 
- NSF Early career - $400k + over five years
- NASA - $240k over three years
- Air Force - $360k over three years
- Navy - $510k over three years
### Related
- [[§Academia Constraints]]





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Benʼs working notes

A new professor needs about $1.5m to get going

A new professor needs about -1-5m to get going

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