Key Lessons from Hamming on Research
Richard W. Hamming’s key lessons about research (from “You and Your Research” ) include: Set yourself high goals—and treat it as your responsibility, not just luck. He argues against the objection that great work is “...
Richard W. Hamming’s key lessons about research (from “You and Your Research” ) include: Set yourself high goals—and treat it as your responsibility, not just luck. He argues against the objection that great work is “all a matter of luck,” and repeats Pasteur’s line “Luck favors the prepared mind,” concluding that you prepare yourself for success “from moment to moment.”[:cite[1]{ln=4}],[:cite[1]{ln=5}],[:cite[1]{ln=6}] Work on important problems, not just busy work. He states that if you “do not work on important problems,” you have little chance of doing important things.[:cite[2]{ln=3}] He also criticizes the observation that many scientists spend most of their time on things they believe are not important.[:cite[3]{ln=3}],[:cite[3]{ln=4}] Build courage/confidence and don’t be overly focused on failures. He calls confidence “an essential property” (also framed as “courage”) and says courage is something you can develop.[:cite[4]{ln=1}],[:cite[4]{ln=5}] He also advises paying less attention to failures than people usually recommend (in the “Learn from your mistakes” framing), using Shannon as an example.[:cite[4]{ln=6}] Hard work matters; inspiration/luck exists, but don’t depend solely on luck. He cites Edison (“99% perspiration and 1% inspiration”) and emphasizes that creative acts come from “hard work…for long years,” while acknowledging luck sometimes happens—yet says it is “folly” to depend solely on luck for the outcome of one life.[:cite[5]{ln=2}],[:cite[5]{ln=3}],[:cite[5]{ln=4}],[:cite[5]{ln=5}] When stuck, change the problem—often by inverting/reformulating it. He shares a lesson that “When stuck, often inverting the problem…represents a significant step forward.”[:cite[6]{ln=1}] In his own story, avoiding an “acre of programmers” by letting machines do mechanical symbol manipulation led him “directly to a frontier of computer science” by inverting the problem.[:cite[7]{ln=2}],[:cite[7]{ln=5}],[:cite[7]{ln=6}] Use “style”: develop the way you think and present your work. He says the essence of the book is “style,” and that the content is the style of thinking shown in examples.[:cite[8]{ln=1}],[:cite[8]{ln=2}] He also stresses “Doing the job with ‘style’ is important,” including recasting your work in a more fundamental form so it can have wider application.[:cite[9]{ln=3}],[:cite[9]{ln=5}] Keep an open mind (tolerate ambiguity): believe and question at the same time. He says great people can “tolerate ambiguity” and “can both believe and disbelieve at the same time.”[:cite[10]{ln=2}] He warns that too much belief prevents seeing chances for improvement, while too little belief leads to doubts and little progress.[:cite[10]{ln=4}] Ask bigger questions regularly rather than staying submerged in details. He “strongly recommend[s] taking the time, on a regular basis, to ask the larger questions” and not remain immersed in detail.[:cite[11]{ln=1}] He frames this as necessary for leadership into the future—repeatedly looking at the bigger picture.[:cite[11]{ln=2}] Ensure others can build on your results—don’t try to be indispensable. He says you should do your work so that “others can build on top of it,” and warns against clinging to exclusive control of an idea, arguing that recognition depends on others using/adapting/extending your results.[:cite[12]{ln=1}],[:cite[12]{ln=2}],[:cite[12]{ln=3}] Great research often needs persistence through long discouragements. He calls “the courage to continue” essential because great research has “long periods with no success and many discouragements.”[:cite[13]{ln=3}]