Science
Interdisciplinary
Which half?
Scientific writing
A tiny rivulet in a distant forest
The downgrading of experience
Humility
Art and science
The Structure of Scientific Revolutions
BLDGBLOG
The Art of Doing Science and Engineering: Learning to Learn
The illustrated guide to a Ph.D.
evermore, and other beautiful things
An Article by Linus the SephistIf all evidence of civilization on Earth was destroyed, and humans had to re-build society from the ground up, what would be different? Feynman reckons that pivotal scientific moments, like the discovery of the atom, will still happen in the same way. Perhaps mathematics will be similarly rediscovered.
Someone told me once in response to this question, no artwork would ever be recreated. The art we create – music, stories, dance, film – isn’t a fundamental element of the universe, or even of humanity. It’s unique to each artist. If you choose to create art, you leave something in the world that has never had a chance to exist before, and will never again have a chance to exist. There will never be another Beatles or Studio Ghibli or Picasso. Art, in its infinite variations of originality, is cosmically unique in a way the sciences will never be. Art immortalizes human experiences that would otherwise vanish in time.
Reality is Very Weird and You Need to be Prepared for That
An EssayWe might be closer than we think to cures for depression, hypertension, and yes, even obesity.
The answer to scurvy was just one thing, plus a few wrinkles — mostly “not all citrus has the antiscorbutic property” and “most animals can’t get scurvy”. This was only difficult because people weren’t prepared to deal with basic wrinkles, but we can do better by learning from their mistakes.
This means don’t give up easily. It suggests that there is lots of low-hanging fruit, because even simple explanations are easily missed.
Lots of theories have been tried, and lots of them have been given up because of something that looks like contradictory evidence. But the evidence might not actually be a contradiction — the real explanation might just be slightly more complicated than people realized. Go back and revisit scientific near-misses, maybe there’s a wrinkle they didn’t know how to iron out.
Tortured phrases
An Article by Holly ElseIn April 2021, a series of strange phrases in journal articles piqued the interest of a group of computer scientists. The researchers could not understand why researchers would use the terms ‘counterfeit consciousness’, ‘profound neural organization’ and ‘colossal information’ in place of the more widely recognized terms ‘artificial intelligence’, ‘deep neural network’ and ‘big data’.
Further investigation revealed that these strange terms — which they dub “tortured phrases” — are probably the result of automated translation or software that attempts to disguise plagiarism. And they seem to be rife in computer-science papers.
Why Most Published Research Findings Are False
A Research Paper by John P.A. IoannidisThere is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance.
A hypothesis is a liability
A Research Paper by Itai Yanai & Martin LercherThere is a hidden cost to having a hypothesis. It arises from the relationship between night science and day science, the two very distinct modes of activity in which scientific ideas are generated and tested, respectively [1, 2]. With a hypothesis in hand, the impressive strengths of day science are unleashed, guiding us in designing tests, estimating parameters, and throwing out the hypothesis if it fails the tests. But when we analyze the results of an experiment, our mental focus on a specific hypothesis can prevent us from exploring other aspects of the data, effectively blinding us to new ideas.
What's Wrong With This Model?
What's wrong with the rational model
- We Don’t Really Know the Goal When We Start
- We Usually Don’t Know the Decision Tree – We Discover It as We Go
- The Nodes Are Really Not Design Decisions, but Tentative Complete Designs
- The Goodness Function Cannot be Evaluated Incrementally
- The Desiderata and Their Weightings Keep Changing
- The Constraints Keep Changing
Deciding what to design
We Don’t Really Know the Goal When We Start
The most serious model shortcoming is that the designer often has a vague, incompletely specified goal, or primary objective. In such cases, the hardest part of design is deciding what to design.
I came to realize that the most useful service I was performing for my client was helping him decide what he really wanted.
Today, we recognize that rapid prototyping is an essential tool for formulating precise requirements. Not only is the design process iterative; the design-goal-setting process is itself iterative. Knowing complete product requirements up front is a quite rare exception, not the norm. Therefore, goal iteration must be considered an inherent part of the design process.
Evaluating goodness
The Goodness Function Cannot be Evaluated Incrementally
The Rational Model assumes that design involves a search of the decision tree, and that at every node, one can evaluate the goodness function of several downward branches. In fact, one cannot in general do this without exploring all the downward branches to all their leaves, which is possible in principle, but leads to a combinatorial explosion of alternatives in practice.
Changing constraints
The Constraints Keep Changing
The explicit listing of known constraints in the design program helps here. The designer can periodically scan the list, asking, “Can this constraint now be removed because the world has changed? Can it be entirely circumvented by working outside the design space?”
They just don't work that way
Perhaps the most devastating critique of the Rational Model, although perhaps the hardest to prove, is that most experienced designers just don’t work that way.
“Conventional wisdom about problem-solving seems often to be contradicted by the behavior of expert designers. Empirical studies of design activity have frequently found ‘intuitive’ features of design ability to be the most effective and relevant to the intrinsic nature of design. Some aspects of design theory, however, have tried to develop counter-intuitive models and prescriptions for design behavior.” — Nigel Cross
We must outgrow it
Why all this fuss about the process model? Does the model we and others use to think about our design process really affect our designing itself? I believe it does. I believe our inadequate model and following it slavishly lead to fat, cumbersome, over-features products and also to schedule, budget, and performance disasters.
The Rational Model, in any of its forms, leads us to demand up-front statements of design requirements. It leads us to believe that such can be formulated. It leads us to make contracts with one another on the basis of enshrined ignorance. A more realistic process model would make design work more efficient, obviating many arguments with clients and much rework.
The Waterfall Model is wrong and harmful; we must outgrow it.