The most memorable answer to this question came from science fiction writer Harlan Ellison, who said “Poughkeepsie” (on checking Wikipedia, I learn that he died a couple of years ago).
But in the context of discussions about remote work, I’m interested in the claim that random physical meetings (the archetypal example being corridor or water-cooler encounters with colleagues) are an important source of ideas, and therefore a reason for not working remotely.
This seems to be the kind of topic for which the data will consist mostly of anecdotes and introspection. A marginal improvement is too look over my own list of publications to see if I can identify any where the source arose from some particular interaction.
Looking at my 100 most-cited papers in Google Scholar, most collaborations are the result of planning rather than chance. In pre-Internet days, most of my collaborations started from seminars and conferences I spoke at or attended because the topic was of interest, or else from direct approaches by a colleague, usually in the same department. From the early 1990s onwards, direct approaches mostly came by email, and work has been done the same way. In several cases, I have written joint papers before ever meeting my co-author(s), though in other cases in-person collaboration with one or two co-authors works better.
More interesting to me, are the cases where the idea has come from blogging. Some notable examples
- My Zombie Economics book. Starting with blog discussions, the idea for a book came from blog commenter Max Sawicky, and was picked up by Seth Ditchik at Princeton UP, who also commissioned Economics in Two Lessons and my current book-in-progress Economic Consequences of the Pandemic
- Cross-disciplinary collaborations with Henry Farrell and LA Paul both arising from my involvement with Crooked Timber
- This paper, which started with a comment on a blog post to the effect that “future generations” are in fact already alive (At least I think that’s how it happened. I could never locate the comment to acknowledge the source.)
It seems to me that that these are much more like the kind of serendipitous links that are supposed to be generated by water coolers.
Of course, academic research is a special kind of work, and I’m much more involved with the Internet than most of my colleagues (or, at least, a few years ahead of the general adoption trend). So, I’d be interested in anecdotes from others and links to actual research, if there is any.
14 thoughts on “Where do you get your ideas?”
(1) Take an important essay, book or thesis, with something original to say, where you greatly admire the writer (usually for clarity and method) but where you ultimately disagree with the overall thesis and final conclusions.
(2) Take an important concept that you do agree with from the guts of that work. Then start working to figure out a better use for that idea by combining it with your own different a prioris and co-theses. See where this synthesis leads.
(3) Use language itself to suggest ideas to you. All ideas possible to you, including possible new ideas, are already available in your lexicon (your total vocabulary). This is a truism of course. Your mind is, among other things, an engine for discovering new ideas by continually rearranging elements of you current vocabulary. Work with that idea in mind.
(4) And of course, drink coffee.
I’m a software engineer so more at the bleeding edge of both technology and social distancing…
I’ve always got most of my ideas from the internet, a few from books and no good ones from in person discussions. My one academic publication was entirely internet based (I primarily have engineering qualifications and a publication in Signs, at the time a journal of Feminist Studies, since retitled “women in culture and society”).
Most of my ideas come from either problems I have (“need a bed”) or seeing things on the internet and going “something a bit like that, but different” and making it. Or at least designing it and paying someone else to make it. I make physical stuff for the most part, rather than writing down ideas. My writing is often documentary for that reason, and the consulting I’ve done from that has mostly been over the internet.
A speculation. The Internet comes in for a lot of stick for sorting us all into like-minded communities, protected from radically discordant views. I never watch Fox News, for instance. But like-minded communities (say the readership of this blog) are precisely the safe environments that foster creativity. I’m exposed here to ideas that are different from mine, but not so different as to constitute a cognitive threat. Under these irritants, my ideas evolve, incrementally. As Kuhn pointed out, most scientific progress takes place within an accepted paradigm, and revolutionary upheavals are very rare. The same holds for the social sciences, arts and humanities. It may be good to be pulled out of one’s comfort zone from time to time. But the value of that lies in defining one’s position and honing one’s rhetorical strategies, not getting new insights.
James, that’s exactly my view.
I am hoping that you have now read “Capital as Power” by Bichler and Nitzan. I think ideas can come from people who have some different ontological a prioris to oneself but where the ideas are not so different that their ontology and your ontology (and methods) have no points of intersection.
I found myself agreeing, after reading Bichler & Nitzan (and Blair Fix), that financial capital has a manifestation as (social) power. Indeed, their term “capital as power” implies that capital as power is just one manifestation of capital. I don’t know if Bichler and Nitzan would agree with me or not but I consider I am correct on this point. Through my ontological theorizing, I have deduced that financial capital at the fundamental ontological levels (inorganic-physical, somatic and neurological levels) is information. There is no contradiction in saying that capital is information and capital is power. Indeed, there is a necessary complementarity. Financial capital is a notional and formal entity and “clumps” of Financial capital are comprised of a numeric quantity (say 1 million) times a notional measure (the counter of the numéraire, usually a dollar) in the “social-fictive” dimension of “value”.
I imagine that you would disagree that economic value is a social-fictive dimension. I imagine that you might consider it is a social-heuristic dimension (of an ordinal nature). That debate alone would lead to a difficult ontological discussion. I am not sure myself how it would be or could be resolved. When are we involved in fictions and when are we involved in heuristics of the real or worthwhile? Our own ordinally ranked moral philosophy values will play a role in this determination. Private property, in the manner proposed by Locke and supported by capitalism, neoliberalism and (American) libertarianism) can be viewed as a fictive claim or social-fictive claim. Thus, whether an “item” is viewed as possessing a fictive dimension without a real or ethical support or a genuine dimension of some kind with a real or at least a genuine consequentialist ethical support, will determine whether we think market heuristic, ordinal or cardinal valuations) can be validly applied. The problem with modern markets would seem to be that they value relative to property law etc. (something you have written often youself) and also that they mix and cross-value “items” which are real at one end of the spectrum and fictive at the other end of the spectrum. This would seem essentially to be a category mistake and perhaps explain at the most fundamental level why market fundamentalism can never work.
I tend to be a fundamentalist in the other direction and to hold or suspect that markets do not work, at least not in the manner claimed by “conventional” market economics. Professor Richard A. Werner’s views are interesting in this regard:
To continue on an earlier tack: In its purest form, financial capital is information. It is a pattern instantiated in a material or energy medium and it is a pattern capable of influencing or generating other patterns through the interpretations and actions of humans (human agents) and computers (computer AI agents). Human agents demonstrate an extensive form of autonomy (complexity and flexibility with regard to instructions and actions) of a kind quite different from the still limited to non-existent autonomy of computer AI agents.
Where living entities, or cells of living agents, are involved as agents, complex patterns which can influence or generate other complex patterns, require a code, a transcriber and/or an interpreter of the code and thence a fabricator of the new complex patterns made according to “instruction” patterns. We can see this occurring with the operations of RNA and DNA in living cells. In that case, consciousness is not required, so far as we can determine. In the case of human minds, which have some consciousness but not what would be called absolute consciousness and self-awareness, these minds act as encoders and decoders of the patterns of language information. (Mathematics is also a language of course.) The human body maybe be regarded as the set of servos (not intending to dehumanize just to be descriptively accurate) which can apply pattern information beyond the body by kinetic means or by language influence. Indeed, kinetics is still involved with language as both sound waves and photos transfer energy and information kinetically.
The important point here is the action of the living agents, the intelligent human beings in this case, as encoders and decoders of information, who then act on the information (in patterns) to create other patterns. The information of financial capital is a legitimizing and facilitating instruction. It legitimizes and facilitates transfers of labor, materials and energies. Also required are plans (plans for a dam for example) to detail how the labor, materials and energies are to be used. Structural engineers are trained to understand plans and requirements for a dam. But how are humans as social agents trained to obey the directives of money and capital?
Let me reiterate that key question. How are humans as social agents trained to obey the directives of money and capital? This gets back to the question of (social) power. It is one thing to be trained in directives. It is another thing to comply. How is compliance generally ensured? This is the point where we discover that mathematics, including the mathematics of economics, is inadequate (IMHO) to give a proper explanation of the origins and derivation of social power. We have to turn to word language.
The more natural and native (perhaps) and solely word-language trained mind is a fuzzy logic machine, not a formal logical or mathematical mind. Its training occurs in actions and words in a largely pre-mathematical milieu. Word language, and thus philosophy in words, containing as they do, nuances and even non-logical contradictions and “fuzziness” or fuzzy logic is/are more naturally attuned to explain the phenomena of inculcation and enculteration. Only if we can explain the inculcation and enculteration of money and capital concepts into humans, can we explain the instantiation of social power in money and capital.
Why do money and capital have (social) power? Training in mathematical literacy cannot alone explain it. That facilitates its technical operations but does not explain its influence and behavioral control over people. To explain that we must depart from mathematical theories and return to moral philosophy theories in words which convey nuance and imprecision (the fuzzy logic more native to the human brain). If capital does not measure value but instead instantiates (social) power (following Bichler, Nitzan and Fix) then how is that instantiation of social power developed?
Here we need to go to five words useful in this context: words which, with their extensive cultural meanings, cannot be mathematized. These words are gift, bribe, inducement, reward and punishment. These are words of a sociological and behavioral study of economics and are more appropriate tools, in my view, to discuss what is given to people when they are given or lose money in our system. If money does not objectively measure value how does it instantiate and develop social power operationally? I argue money and capital do this by being one or more of a gift, bribe, inducement, reward or punishment (negative values for punishment). The money system is combined with other systems like the property system and the state violence system to ensure that all capital-appropriate rewards and punishments are delivered. We are trained by gifts, bribes, inducements, rewards and punishments to accede to this system. As a totalizing system it takes control of us. We are servants of the overall notional machine of capital just as we became and become servants of the physical machines of the system. We are not Pavlov’s dogs. We are capital’s dogs. Some sub-cultures would say, perhaps with a misogynistic side-slur unfortunately, that we are capital’s bitches. This is true if we are workers or indigent.
The money payed to a day laborer does not value his labor in any way truly equatable to the money values of other things. It simply induces him or her to work. It is an inducement not a valuation. The price of labor is an administered price not a market price. A higher rate to do very difficult or dangerous work is a bribe or pay-off of sorts. The amounts needed to induce or bribe are relative to the precarity of the day laborer’s existence. They are not relative to the “values” of other goods and services in the market system.
In the end, political economy must turn to moral philosophy and to democratic and direct action. Words and actions, not mathematics, will be found to be the methods most conformable to the remedying of unjust and unsustainable personal and social empirical realities in a complex, open-ended, emergent, and fuzzy-phenomena world. IMHO, reserve mathematics for administration and science. Administration will include administered prices in a setting which ensures the just and equitable meeting of needs, basic and advanced, for every person in society.
Just my views, but I think they have some ontological and moral validity, otherwise I wouldn’t hold them of course. 🙂
I can’t believe the mass of junk media out there with the resultant bizarre eg Tony Abbott to the UK, COVID is a chinese plot, vaccinations will kill you.
I’m now resigned to a Trump return, maybe even by a landslide – I’m finding some solace in real books by real people viz Emile Zola, Mrs Robert Henrey, Hisham Matar et al – the long forgotten book repository has been rediscovered.
Very interesting post James.
John, Try to Remember: Thanks for the endorsements. But with no “buts”, you didn’t learn anything from me. No grain of sand, no pearl.
Where did this idea of innovationn come from, and the thinking behing it?
Innovation used mendaciously.
“In its interim report, tabled in Parliament on Wednesday night, the Committee said: “Because innovation like ‘buy now, pay later’ often occurs on the fringes of regulation, it is inappropriate to force each innovation into a one-size-fits-all approach.”
“It said, “industry self-regulation provides an initial framework to protect innovation which can later be backed up by a policy statement” by the Federal Government”…
My question – when since 5,000bc was buy now pay later first used?
Zog to Zeg: “have masterdon leg now – give me back leg next moon”
Idea JQ > AI > economics… and experimentation with AI researchers + team and findings of Epistemic & Personal Transformation: Dealing with the Unknowable and Unimaginable.
“Measuring hardware overhang
+ Discussion Conclusion and future research proposals
“Crossposted from the AI Alignment Forum. May contain more technical jargon than usual.
…” I would be interested in researching this scaling relation for other problems outside of chess, such as voice and image recognition. Most problems are harder to measure and benchmark than chess. Will the scalings show a similar 2-3 orders if magnitude software overhang? Most certainly, many problems will show similar diminishing returns (or a cap) due to RAM restrictions and wait time. For example, you just can’t run a self-driving car on an Atari, no matter how good the algorithms. I would be interested in researching the scaling for other AI and ML fields, possibly leading to an academic paper”
Why we shouldn’t study what we love
Uncategorized August 14, 2020 4 Minutes
I recognize that I could only start to write about this … once I related to it. I dislike myself for this; my scholarly pride likes to think I can write about the unrelatable, too. Eric Schliesser
…” So my point about not studying what you like is a point about learning, learning to get oneself into a certain mode of reading. Put more fancily: learning to do a certain way of (history of) philosophy. Being passionate about some work or way of thinking is something that is in need of explanation, just as much as not being passionate and feeling unfamiliar about something needs explaining. Such explanations are greatly aided by alienation. As I said in an earlier post, a crucial effect of alienation is a shift of focus. You can concentrate on things that normally escape your attention: the logical or conceptual structures for instance, ambiguities, things that seemed clear get blurred and vice versa. In this sense, logical formalisation or translation are great tools of alienation that help you to raise questions, and generally take an explanatory stance, even to your most cherished texts.”…
Only those who are capable of silliness can be called truly intelligent.
— Christopher Isherwood, born in 1904
The Art Of Creative Thinking: 89 Ways To see Things Differently by Rod Judkins Book Summary & PDF
The Art of Creative Thinking Summary
1. See what happens when you make something happen
2. Be a beginner forever
3. Blame Michelangelo
4. Be committed to commitment.
5. Be the medium of your medium
6. Don’t be someone else
7. Be a generator
8. Be positive about negatives
9. Don’t think about what others think about
10. Doubt everything all the time
11. Feel inadequate
12. Be practically useless
13. Be perceptive about perception
14. Be naturally inspired
15. Don’t be an expert on yourself
16. Be Stubborn about compromise
17. Be a weapon of mass creation
18. Get into what you’re into
19. Cut it out
20. Grow up without growing old
21. If it ain’t broke, break it
22. Pick yourself up
23. Challenge the challenging
24. Find out how to find out
25. Leave an impression
26. Design a difference
27. Be as incompetent as possible
28. Maintain momentum
29. Make the present a present
30. Be mature enough to be childish
31. Aspire to have no goals
32. Open your mind
33. Pause for thoughtlessness
34. Plan to have more accidents
35. If you can’t be really good, be really bad
36. Raise the dead
37. Be a conservative revolutionary
38. Work the hours that work for you
39. Search without finding
40. Don’t overlook the overlooked
41. Put the right thing in the wrong place
42. Stay hungry
43. Surprise yourself
44. Suspend judgment
45. Take advantage of a disadvantage
46. Throw truth bombs
47. Throw yourself into yourself
48. Use shock of awe
49. Value Obscurity
50. Value shared values
51. If something isn’t broken, fix it
52. Light a fire in your mind
53. Discover how to discover
54. To stand out, work out what you stand for
55. To achieve something, do nothing
56. Get into credit
57. Search high and low
58. Mine your mind
59. Look forward to disappointment
60. Think with your feelings
61. Bring chaos to order
62. Take what you need
63. Remake, then remake the remake
64. Be curious about curiosity
65. Become anonymous
66. Achieve the perfect work-life balance
67. Make what you say unforgettable
68. Don’t experiment, BE an experiment
69. Stop missing opportunities
70. Contradict yourself more often
71. Look over the horizon
72. Immerse yourself
74. Take jokes seriously
75. Go from a to b via z
76. Never leave improvisation to chance
77. Reject acceptance and accept rejection
78. Be as annoying as possible
79 Get out of your mind
80. Stay playful
81. Don’t follow the herd
82. Project yourself into the future
83. Box your way out of boxes
84. To learn, teach
85. Be an everyday radical
86. Make freedom a career
87. Be alone with “Friends”
88. Look at the overlooked
89. Rename yourself
Think about your thinking
A good idea from Peter Turchin’s Evolution Institute.
…” The vulnerability of individuals to a viral invasion of their bodies is affected by the sociocultural formations in which they live their lives. In general, wealthy people can afford to use sociocultural systems to protect their bodies, whereas the opposite is true for those without resources. Stratification thus distributes yet another resource unequally: the ability to protect the body from invasion by pathogens.”…
Natural and Sociocultural Selection: Analyzing the Failure to Respond to the C-19 Pandemic
By Jonathan H. Turner
…” As Figure 1 outlines, individual phenotypes and genotypes are successively embedded in groups, organizations, communities, institutional systems, societies, and inter-societal systems. Darwinian selection works only on individual phenotypes (and underlying genotypes), whereas sociocultural selection can work at each and every level of the many sociocultural systems organizing human bodies in their daily activities. These sociocultural systems represent additional protections to human phenotypes, but if these sociocultural phenotypes are inefficient, they greatly increase the chances of a virus spreading across a population and killing many individuals.
…” Societies that seek to erect barriers — for example, by restricting the flow of ideas — will find it tougher to withstand sudden shocks than will those that are open to sharing what they know, from genome sequences and clinical-trial results to designs for personal protective equipment and source code for contact-tracing apps.
“The question is whether the intended audience of politicians and policymakers is ready to listen. Right now, it is hard to see the leaders of the G20 nations pivoting to adopt a more collegial approach to dealing with the pandemic. “…
15 SEPTEMBER 2020
“Keep collaboration open when doors are closing
“As some countries begin to raise barriers to international collaboration, scientists in the S20 engagement group are right to keep them down.”…