Algorithms Quotes

“An algorithm must be seen to be believed.”
― Donald Knuth, Leaders in Computing: Changing the digital world

“Perhaps the most important principle for the good algorithm designer is to refuse to be content.”
― Alfred V. Aho

“In algorithms, as in life, persistence usually pays off.”
― Steven S. Skiena, The Algorithm Design Manual

“Algorithms are not arbiters of objective truth and fairness simply because they're math.”
― Zoe Quinn, Crash Override: How Gamergate (Nearly) Destroyed My Life, and How We Can Win the Fight Against Online Hate

“The greater the uncertainty, the bigger the gap between what you can measure and what matters, the more you should watch out for overfitting - that is, the more you should prefer simplicity”
― Tom Griffiths, Algorithms to Live By: The Computer Science of Human Decisions

“Dawes observed that the complex statistical algorithm adds little or no value. One can do just as well by selecting a set of scores that have some validity for predicting the outcome and adjusting the values to make them comparable (by using standard scores or ranks). A formula that combines these predictors with equal weights is likely to be just as accurate in predicting new cases as the multiple-regression formula that was optimal in the original sample. More recent research went further: formulas that assign equal weights to all the predictors are often superior, because they are not affected by accidents of sampling.”
― Daniel Kahneman, Thinking, Fast and Slow

“Maths is at only one remove from magic.”
― Neel Burton

“The result will not be an Orwellian police state. We always prepare ourselves for the previous enemy, even when we face an altogether new menace. Defenders of human individuality stand guard against the tyranny of the collective, without realising that human individuality is now threatened from the opposite direction. The individual will not be crushed by Big Brother; it will disintegrate from within. Today corporations and governments pay homage to my individuality, and promise to provide medicine, education and entertainment customised to my unique needs and wishes. But in order to so, corporations and governments first need to break me up into biochemical subsystems, monitor these subsystems with ubiquitous sensors and decipher their working with powerful algorithms. In the process, the individual will transpire to be nothing but a religious fantasy. Reality will be a mesh of biochemical and electronic algorithms, without clear borders, and without individual hubs.”
― Yuval Noah Harari, Homo Deus: A History of Tomorrow

“Dataism adopts a strictly functional approach to humanity, appraising the value of human experiences according to their function in data-processing mechanisms. If we develop an algorithm that fulfils the same function better, human experiences will lose their value. Thus if we can replace not just taxi drivers and doctors but also lawyers, poets and musicians with superior computer programs, why should we care if these programs have no consciousness and no subjective experiences? If some humanist starts adulating the sacredness of human experience, Dataists would dismiss such sentimental humbug. ‘The experience you praise is just an outdated biochemical algorithm. In the African savannah 70,000 years ago, that algorithm was state-of-the-art. Even in the twentieth century it was vital for the army and for the economy. But soon we will have much better algorithms.”
― Yuval Noah Harari, Homo Deus: A History of Tomorrow

“So if an algorithm is an idealized recipe, a program is the detailed set of instructions for a cooking robot preparing a month of meals for an army while under enemy attack,”
― Kernighan Brian W.

“Our search for the Master Algorithm is complicated, but also enlivened, by the rival schools of thought that exist within machine learning. The main ones are the symbolists, connectionists, evolutionaries, Bayesians, and analogizers. Each tribe has a set of core beliefs, and a particular problem that it cares most about. It has found a solution to that problem, based on ideas from its allied fields of science, and it has a master algorithm that embodies it.”
― Pedro Domingos, The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World

“The next question is how? How does news find us?
What you need is a certain critical literacy about the fact that you are almost always subject to an algorithm. The most powerful thing in your world now is an algorithm about which you know nothing about.”
― Kelly McBride

“An algorithm is a methodical set of steps that can be used to make calculations, resolve problems and reach decisions. An algorithm isn’t a particular calculation, but the method followed when making the calculation.”
― Yuval Noah Harari, Homo Deus: A History of Tomorrow

“The idea that humans will always have a unique ability beyond the reach of non-conscious algorithms is just wishful thinking. The current scientific answer to this pipe dream can be summarised in three simple principles: 1. Organisms are algorithms. Every animal – including Homo sapiens – is an assemblage of organic algorithms shaped by natural selection over millions of years of evolution. 2. Algorithmic calculations are not affected by the materials from which you build the calculator. Whether you build an abacus from wood, iron or plastic, two beads plus two beads equals four beads. 3. Hence there is no reason to think that organic algorithms can do things that non-organic algorithms will never be able to replicate or surpass. As long as the calculations remain valid, what does it matter whether the algorithms are manifested in carbon or silicon?”
― Yuval Noah Harari, Homo Deus: A History of Tomorrow

“There are simply several different paths leading to high intelligence, and only some of these paths involve gaining consciousness. Just as airplanes fly faster than birds without ever developing feathers, so computers may come to solve problems much better than mammals without ever developing feelings. True, AI will have to analyse human feelings accurately in order to treat human illnesses, identify human terrorists, recommend human mates and navigate a street full of human pedestrians. But it could do so without having any feelings of its own. An algorithm does not need to feel joy, anger or fear in order to recognise the different biochemical patterns of joyful, angry or frightened apes.”
― Yuval Noah Harari, 21 Lessons for the 21st Century

“Digital dictatorships are not the only danger awaiting us. Alongside liberty, liberal order has also set great store by the value of equality. Liberalism always cherished political equality, and it gradually came to realise that economic equality is almost as important. For without a social safety net and a modicum of economic equality, liberty is meaningless. But just as Big Data algorithms might extinguish liberty, they might simultaneously create the most unequal societies that ever existed. All wealth and power might be concentrated in the hands of a tiny elite, while most people will suffer not from exploitation, but from something far worse – irrelevance.”
― Yuval Noah Harari, 21 Lessons for the 21st Century

“So we had better call upon our lawyers, politicians, philosophers and even poets to turn their attention to this conundrum: how do you regulate the ownership of data? This may well be the most important political question of our era. If we cannot answer this question soon, our sociopolitical system might collapse. People are already sensing the coming cataclysm. Perhaps this is why citizens all over the world are losing faith in the liberal story, which just a decade ago seemed irresistible.
How, then, do we go forward from here, and how do we cope with the immense challenges of the biotech and infotech revolutions? Perhaps the very same scientists and entrepreneurs who disrupted the world in the first place could engineer some technological solution? For example, might networked algorithms form the scaffolding for a global human community that could collectively own all the data and oversee the future development of life? As global inequality rises and social tensions increase around the world, perhaps Mark Zuckerberg could call upon his 2 billion friends to join forces and do something together?”
― Yuval Noah Harari, 21 Lessons for the 21st Century

“The likelihood that computer algorithms will displace archaeologists by 2033 is only 0.7 per cent, because their job requires highly sophisticated types of pattern recognition, and doesn’t produce huge profits. Hence it is improbable that corporations or government will make the necessary investment to automate archaeology within the next twenty years.”
― Yuval Noah Harari, Homo Deus: A History of Tomorrow

“The crucial problem isn’t creating new jobs. The crucial problem is creating new jobs that humans perform better than algorithms”
― Yuval Noah Harari, Homo Deus: A History of Tomorrow

“So far we have looked at two of the three practical threats to liberalism: firstly, that humans will lose their value completely; secondly, that humans will still be valuable collectively, but they will lose their individual authority, and will instead be managed by external algorithms. The system will still need you to compose symphonies,”
― Yuval Noah Harari, Homo Deus: A History of Tomorrow

“Data Scientists should recall innovation often times is not providing fancy algorithms, but rather value to the customer.”
― Damian Mingle

“As soon as an Analytical Engine exists, it will necessarily guide the future course of the science. Whenever any result is sought by its aid, the question will then arise — by what course of calculation can these results be arrived at by the machine in the shortest time?”
― Charles Babbage, Passages from the Life of a Philosopher

“Eventually, we may reach a point when it will be impossible to disconnect from this all-knowing network even for a moment. Disconnection will mean death. If medical hopes are realised, future people will incorporate into their bodies a host of biometric devices, bionic organs and nano-robots, which will monitor our health and defend us from infections, illnesses and damage. Yet these devices will have to be online 24/7, both in order to be updated with the latest medical news, and in order to protect them from the new plagues of cyberspace. Just as my home computer is constantly attacked by viruses, worms and Trojan horses, so will be my pacemaker, my hearing aid and my nanotech immune system. If I don’t update my body’s anti-virus program regularly, I will wake up one day to discover that the millions of nano-robots coursing through my veins are now controlled by a North Korean hacker.”
― Yuval Noah Harari, Homo Deus: A History of Tomorrow

“You want to know who you really are?’ asks Dataism. ‘Then forget about mountains and museums. Have you had your DNA sequenced? No?! What are you waiting for? Go and do it today. And convince your grandparents, parents and siblings to have their DNA sequenced too – their data is very valuable for you. And have you heard about these wearable biometric devices that measure your blood pressure and heart rate twenty-four hours a day? Good – so buy one of those, put it on and connect it to your smartphone. And while you are shopping, buy a mobile camera and microphone, record everything you do, and put in online. And allow Google and Facebook to read all your emails, monitor all your chats and messages, and keep a record of all your Likes and clicks. If you do all that, then the great algorithms of the Internet-of-All-Things will tell you whom to marry, which career to pursue and whether to start a war.”
― Yuval Noah Harari, Homo Deus: A History of Tomorrow

“When we go online, we commit ourselves to the care of online mechanisms. Digital Band-Aids for digital wounds. We feed ourselves into machines, hoping some algorithm will digest the mess that is our experience into something legible, something more meaningful than the "bag of associations" we fear we are.”
― Michael Harris

“Effective algorithms make assumptions, show a bias toward a simple solutions, trade off the costs of error against the cost of delay, and take chances.”
― Brian Christian, Tom Griffiths

“We will start by sketching the recursive algorithm and then add details to get to a full description of the algorithm. Footnote : Translation: We will add details till the mess becomes both undecipherable and incomprehensible at the same time. Hopefully, the inner poetical and rhythmical beauty of the text will keep the reader going.”
― Sariel Har-Peled, Geometric Approximation Algorithms (Mathematical Surveys and Monographs)

“We have to learn to interrogate our data collection process, not just our algorithms.”
― Cathy O'Neil, Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy