The Value of Culture

For without culture or holiness, which are always the gift of a very few, a man may renounce wealth or any other external thing, but he cannot renounce hatred, envy, jealousy, revenge. Culture is the sanctity of the intellect. William Butler Yeats, 1909

Culture is one of those slippery words everyone talks about but no one talks about in the same way. The etymology stems from the Middle French culture, meaning “the tilling of land,” itself from the Latin cultura (which shares roots with colony)It wasn’t until 1867 that culture was regularly used to describe the collective customs and achievements of a people. I haven’t confirmed this, but suspect this figurative use of the word occurred so late in history because what we currently call culture used to be called mores, the habits and customs that define the ethical norms of a community. Note that culture connotes activity, cultivation, education, the conscious act of shaping one’s activity to embody a certain set of values; mores connotes manners, customs, habit, the subconscious adoption of patterns set and reflected by others and ancestors. It’s possible–but again requires further research–that culture became the word used to describe the how of human activity in tandem with the rise of the autonomous, capitalist individual.

In the workplace, culture often gets reduced to the fluffy stuff of the HR department. At its most vapid, culture is having a cool office full of razor scooters, organic smoothies, and, as Dan Lyons mordantly and hilariously describes in the prologue to Disrupted, an aesthetic that “bears a striking resemblance to [a Montessori preschool]: lots of bright basic colors, plenty of toys, and a nap room with a hammock and soothing palm tree murals on the wall. The office as playground trend that started at Google and has spread like an infection across the tech industry.” Work as lifestyle, where every sip of Blue Bottle coffee signals our coolness, where every twist of wax on our mustaches imbues our days with mindful meaning as we hack our brains and the establishment (ignoring, for the time being, the premium we pay for those medium roast beans). At its most sinister, culture is overlooking implicit and even explicit acts of harassment, abuse, or misogyny to exclusively favor the ruthless promotion of growth (see Uber’s recent demise). At its most awkward, culture is the set of trust- and bond-building exercises conducted during the offsite retreat, where we do cartwheels and jumping jacks and sing Kumbaya holding hands in a circle once a year only to return to the doldrums at our dark mahogany corner offices and linoleum cubicles on Monday morning. At its most sinuous, culture is the set of minute power plays that govern decisions in a seemingly flat organization, the little peaks of hierarchy that arise no matter how hard we try to proclaim equality, the acrid taste we get after meetings when it’s obvious to everyone, although no one admits it, that deep down our values aren’t really aligned, and that master-slave dialectics always have and always will shape the course of history.

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The candy wall is considered a perk for the millennial workforce at Hubspot.

But culture can be much more than craft beer at hack night and costumes on Halloween. The best businesses take culture so seriously that it shifts from being an epiphenomenon to weaving the fabric of operations. The moment of transubstantiation takes place when a mission statement changes from being a branding tool to being a principle for making decisions; when leadership abandons micromanagement to guide employees with a north star, enabling ownership, autonomy, and creativity; when the little voices of doubt and fear and worry and concern inside our heads are quieted by purpose and clarity, when we feel safe to express disagreement without suffering and repercussion; when a whole far greater than the sum of its parts emerges from the unique and mystically aligned activities of each individual contributor.

This post surveys five companies for which culture is an integral part of operations. Each is inspiring in its own way, and each thinks about and pragmatically employs culture differently at a different phase of company history and growth.

Always Day 1: True Customer Obsession at Amazon

On April 12, Jeff Bezos released a letter to shareholders. Amazon is now 23 years old, and has gone from being an online bookstore to being the cloud infrastructure making many startups possible, the creator of the first convenience store without checkout lines, and one of the largest retailers in the world. Given its maturity and the immense scope of its operations, Amazon risks falling into big company traps, succumbing to the inertia of process and the albatross weight of the innovator’s dilemma. Such “Day 2” stupor is precisely what CEO Jeff Bezos wants to avoid, and his letter presents four cultural pillars to keeping a big company running like a small company: customer obsession, a skeptical view of proxies, the eager adoption of external trends, and high-velocity decision making.

Bezos states “true customer obsession” as the fulcrum guiding Amazon’s business. While this may seem like a given, in practice very few companies succeed at running a customer-centric business. As Bezos points out, businesses can be product focused, technology focused, or business model focused. They can be sales focused or lifestyle focused. They can focus on long-term strategy or short-term revenue. The popularity and design thinking stems from the fact that product development methodologies historically struggled to take into account how users reacted to products. In Creative Confidence, Tom Kelley and David Kelley show multiple examples of how feature prioritization decisions change when engineers leave the clean world of verisimilitude to enter the messy, surprising world of human reactions and emotions. One of my favorite examples in the Kelleys’ book is when Doug Dietz, an engineer at GE Healthcare, overhauled his strategy for building MRIs when he realized the best technical solution created a horrifying experience for children. The guiding architecture for MRIs henceforth became pirate ships or space ships, contextual vessels that could channel the imagination to dampen the aggressive clanging of the machine, and create a more positive experience for sick children.

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GE’s pirate ship MRI, designed to make tests less horrifying for children.

Bezos astutely remarks that a customer-centric approach forces a company to stay innovative and uphold the hunger of Day 1 because “customers are always beautifully, wonderfully dissatisfied, even when they report being happy and business is great.” This is Marketing with a big M. Not marketing as many people misunderstand it, i.e., as the use of catch phrases or content to shape the opinions of some group of people in the hope that these shaped opinions can transform into revenue, but marketing as a sub-discipline of empiricism, where a company carefully observes the current habits of some group of people to discern a need they don’t yet have, but that they will willingly and easily recognize as a need, and change their habits to accommodate, once it’s presented as a possibility. Steve Jobs did this masterfully.

Using customers as an anchor to design and build new products is powerful because truth is stranger than fiction. Many product managers and engineers fall into the trap of verisimilitude, making products as they would write a play, where each detail seems to make sense in the context of the coherent whole. I’ve seen numerous companies spend months imagining features they think users will want that arise logically from the technical capabilities of a tool, only to realize meager revenues because users actually want something different. User stories built on real research with real people–even if it’s a sample set of a few rather than the many that support A/B testing methodologies at consumer companies like Netflix–have Sherlock Holmes superpowers, leading to insights that aren’t obvious until reinterpreted retrospectively.

Bezos ends his letter with the importance of high-velocity decision making, which involves the courage to make decisions with 70% of the information you wish you had and “disagreeing and committing” when consensus is impossible. Disagreeing and committing requires radical candor and the courage to embrace conflict head on. Early in my career, I failed on a few occasions by not having the courage to voice disagreement as we made certain important decisions; after the fact, when we started to observe the negative impacts of the decision, I wanted to stand up and say “I told you so!” but couldn’t because it was too late. This breeds resentment, and it certainly takes culture work to make employees feel like they can voice conflicting or dissenting views without negative repercussion.

(A couple of my readers pointed out that Amazon has been reported to have a cutthroat culture. This reminds me of Ferdinand Céline and Martin Heidegger, two men who supported Fascism and Nazism, and yet left us quite valuable writings. Should we pay attention to the idealized version of a man or company, the traces left in letters and prose, or the reality of his lived life and actions? Can we forgive the sinner if he leaves us gold?)

Soul as a Recruiting Tool at

While Amazon is a massive company whose cultural challenge is to avoid inertia and bureaucracy, is a brand-new startup whose challenge is to attract the right early talent that will make or break company success. Inspired by his experience at Facebook, CEO & Founder Steve Irvine decided the surest way to recruit top talent–and avoid hires whose values were misaligned–was to make it a priority to build a company with soul.

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While we easily recognize that Ray Charles has more soul than Justin Bieber,                    we struggle to quantify soul in company culture.

In a recent presentation, Irvine explains how soul is the hard-to-explain, intangible aspect of a business people struggle to pin down in words, one of those things you know when you see it but can’t really articulate or describe. He says it’s “what you do when no one is looking and when everyone is looking, what gives people in your company purpose and makes them brave in the face of long odds.” Underlying soul is a set of common values: Irvine believes its crucial that everyone in a company share values and mission, even if they approach different questions with a plurality and diversity of perspectives. Soul, here, is different from the spiritual essence of an individual, the self that remains after our corporeal bodies return to dust. It’s the least common denominator uniting a group of diverse individuals, the fulcrum that keeps everyone engaged when things aren’t going well, the life force sustaining interest and passion in the midst of doubt and dismay.

Perhaps most interesting is how effective commitment to soul can be. Irvine is at the very beginning of building his company, so soul, for the moment, is an abstract promise rather than an embodied commitment. But it’s extremely powerful to love what you do. To embrace work with passion, not just as a job that pays the bills. To be excited about weathering storms together with a group of people you care about and in the service of a mission you care for. The trick is to transform this energy into the hard work of building a business.

IKEA: The Best Company Mission Statement Ever

If there’s anyone who has managed to transform soul into successful operations, it’s IKEA founder Ingvar Kamprad. The Testament of a Furniture Dealer, which he wrote in 1976, is the most powerful company mission statement I’ve ever read. It’s powerful because it shows how the entirety of IKEA’s operations result, as if by logical necessity, from the company’s core mission “to create a better everyday life for the many people.”

Just after stating this core mission, Kamprad continues that they will achieve this mission “by offering a wide range of well-designed, functional home furnishing products at prices so low that as many people as possible will be able to afford them.” These two initial phrases function like axioms in a mathematical proof, with subsequent chapter in the Testament exploring propositions that logically follow from the initial axioms.

The first proposition regards what Kamprad calls product range, the set of products IKEA will and won’t offer. As the many people need to furnish not just their living rooms but their entire homes, IKEA’s objective must, as a result, “encompass the total home environment, [including] tools, utensils and ornaments for the home as well as more or less advanced components for do-it-yourself furnishing and interior decoration.” The product design must be “typically IKEA,” reflecting the company’s way of thinking and “being as simple and straightforward as ourselves.” The quality must be high, as the many people cannot afford to just throw things away.

To keep costs low, of course, requires “getting good results with small or limited resources.” Which, by logical necessity, leads to subsequent propositions about the cost of capital and inventory management. Kamprad says that “expensive solutions to any kind of problem are usually the work of mediocrity.” Rigorous pragmatism, and having a sense for the entire supply chain of costs to create and distribute a product, is a core part of IKEA’s culture. Considering waste of resources to be “one of the greatest diseases of mankind,” Kamprad builds the cultural mindset that leads to the compact, do-it-yourself assembly packaging for which IKEA is famous.

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IKEA created this Poäng series in 1976, the same year Kamrad wrote   The Testament of a Furniture Dealer

And the brilliance continues. Kamprad pivots from simplicity in design and production to simplicity as a virtue in decision making, claiming, like Bezos, that “exaggerated planning is the most common cause of corporate death” and extolling a rigorous curiosity that always asks why things are done a given way to open the critical curiosity required to identify opportunities to do things differently. He extols concentration, the discipline required to focus on the specific range of products that defines core identity, the type of focus Steve Jobs instilled to usher Apple to its current level of success. And finally, Kamprad closes his mission by celebrating incompletion and process:

“The feeling of having finished something is an effective sleeping pill. A person who retires feeling that he has done his bit will quickly wither away. A company which feels it has reached its goal will quickly stagnate and lose its vitality.

Happiness is not reaching your goal. Happiness is being on the way. It is our wonderful fate to be just at the beginning. In all areas. We will move ahead only by constantly asking ourselves how what we are doing today can be done better tomorrow. The positive joy of discovery must be our inspiration in the future too.

The word impossible has been deleted from our dictionary and must remain so.”

Note that he wrote this in 1976, a good 35 years before the current new-age thinking focusing on the joy of the process was commonplace wisdom. Note the parallels with Bezos, how both leaders focus on creativity, discipline, and the ruthless awareness and avoidance of biases as a means to keep innovation alive. IKEA has grown from being a low-cost furniture provider in Europe to being a global franchise business with operations in many markets. Time will tell what it will mean for them to serve the many people in the future, and how they will expand their product range while adhering to the focus and discipline required to keep their identity and mission intact.

Commitment to Diversity at Fast Forward Labs

On February 23, 2017, Hilary Mason, the founder and CEO of Fast Forward Labs, sent the following email to our team:

Subject: Maintaining a Respectful Environment


It’s very important to me that our office is respectful and comfortable for everyone who works here and for our visitors, many of whom we are trying to engage as customers and collaborators.


There is writing on the seat to remind you.

Thank you,

Diversity can easily become a compliance checklist item or a pat-yourself-on-the-back politically correct platitude. Practicing it fully takes vigilance and effort. Mason actively promotes diversity and equality in just about every aspect of her professional (and private) existence. Fast Forward Labs is a small company, but there are many women on the leadership team and research interns from international creeds, races, and backgrounds. I’ve sometimes overlooked gender equality (even though I’m a woman myself!) when recommending speakers for conferences, only to have Mason remind me to be mindful in my choices next time around to help build the future we want and can be proud of. We make sure to include a section on ethics in each of our machine learning research reports and have actively turned down business with organizations whose values contrast highly with our own.
The vast majority of the technology world is still run by white men, leading to narratives about the singularity and the superintelligent future that distract us from the real-world ethical problems we face today. We need more women-run companies like Fast Forward Labs to bring more voices to the table and, pragmatically, to make sure character traits like empathy are keeping us on track to solve the right problems and encourage AI adoption (as I discussed in a recent interview on TWiML). This is certainly not to say that empathy is a uniquely feminine trait; but it is to say that no large enterprise will adopt AI successfully without navigating the emotional and people challenges that attend any change management initiative.
(Mason read this post, and told me she doesn’t consider herself to be promoting diversity, but to be creating the world she wants to live in.)

Culture as Product at Asana

The final example focuses on practices to make culture a critical component of a business as opposed to an office decoration or afterthought at the company party. Asana, which offers a SaaS project-management tool, has received multiple accolades for its positive culture, including a rare near-perfect rating on Glassdoor. Short of using Putin-style coercion and manipulation techniques, how did they achieve such positive employee ratings on culture and experience?

According to a recent Fast Company article, by “treating culture as a product that needed to be carefully designed, tested, debugged, and iterated on, like any other product they released.” Just as Amazon analyzes feedback from their external market, so too does Asana analyze feedback from their internal market, soliciting feedback from employees and “debugging” issues like false empowerment as soon as they arise. The company also offers the standard cool office perks that are commonplace in the valley, offering each employee $10,000 (!!!) to set up customized workplaces that can include anything from standing desks to treadmills.

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Asana states its cultural values on its company page.

It’s likely risky to adopt Asana’s culture as product model given the gimmick of hacking phenomena–like our minds and cultural practices–that aren’t computer code. But the essence here is to manage culture using the tools you know well. Agile software development practices aren’t universal across all companies, so it would be a stretch to apply them in environments where they’re not a great fit. But if we take this to a more abstract and general level, it does make sense to treat culture as a living, moving, dynamic product that requires work and discipline just like the products a business offers to its customers, and to manage it accordingly.


The older I get, the more I’m convinced that the how of activity is more important to happiness than the what of activity. Culture is the big how of a company that emerges from the little hows of each individual’s daily activities. When norms were mores, the how was inherited and given, habits and manners we had to adopt to align civil interaction. Now that norms are culture, we’re empowered to create our how, to have it trickle down from mission into operations or work actively to build it and debug it like a product. This requires vigilance, mindfulness, responsibility. It requires humbleness and, as Ingvar Kamprad concludes, “the ambition to develop ourselves as human beings and co-workers.”

The image is from Soup Addict’s recipe for a wild yeast sourdough starter. It’s valuable for us to remember the agricultural roots of the world culture, to bring things back to earth and remember the hard work required to care for something larger than and different from ourselves, which, once it reaches maturity, can feed and nourish us.

Five Distractions in Thinking about AI

One of the main arguments the Israeli historian Yuval Noah Harari makes in Sapiens: A Brief History of Humankind is that mankind differs from other species because we can cooperate flexibly in large numbers, united in cause and spirit not by anything real, but by the fictions of our collective imagination. Examples of these fictions include gods, nations, money, and human rights, which are supported by religions, political structures, trade networks, and legal institutions, respectively.* | **

As an entrepreneur, I’m increasingly appreciative of and fascinated by the power of collective fictions. Building a technology company is hard. Like, incredibly hard. Lost deals, fragile egos, impulsive choices, bugs in the code, missed deadlines, frantic sprints to deliver on customer requests, the doldrums of execution, any number of things can temper the initial excitement of starting a new venture. Mission is another fiction required to keep a team united and driven when the proverbial shit hits the fan. While a strong, charismatic group of leaders is key to establishing and sustaining a company mission, companies don’t exist in a vacuum: they exist in a market, and participate in the larger collective fictions of the Zeitgeist in which the operate. The borders are fluid and porous, and leadership can use this porousness to energize a team to feel like they’re on the right track, like they’re fighting the right battle at the right time.

These days, for example, it is incredibly energizing to work for a company building software products with artificial intelligence (AI). At its essence, AI is shorthand for products that use data to provide a service or insight to a user (or, as I argued in a previous post, AI is whatever computers cannot do until they can). But there wouldn’t be so much frenzied fervor around AI if it were as boring as building a product using statistics and data. Rather, what’s exciting the public are the collective fictions we’re building around what AI means–or could mean, or should mean–for society. It all becomes a lot more exciting when we think about AI as computers doing things we’ve always thought only humans can do, when they start to speak, write, or even create art like we do, when we no longer have to adulterate and contort our thoughts and language to speak Google or speak Excel, going from the messy fluidity of communication to the terse discreteness of structured SQL.

The problem is that some of our collective fictions about AI, exciting though they may be, are distracting us from the real problems AI can and should be used to solve, as well as some of the real problems AI is creating–and will only exacerbate–if we’re not careful. In this post, I cover my top five distractions in contemporary public discourse around AI. I’m sure there are many more, and welcome you to add to this list!

Distraction 1: The End of Work

Anytime he hears rumblings that AI is going to replace the workforce as we know it, my father, who has 40 years of experience in software engineering, most recently in natural language processing and machine learning, placidly mentions Desk Set, a 1957 romantic comedy featuring the always lovable Spencer Tracy and Katharine Hepburn. Desk Set features a group of librarians at a national broadcasting network who fear their job security when an engineer is brought in to install EMERAC (named after IBM’s ENIAC), an “electronic brain” that promises to do a better job fielding consumer trivia questions than they do. The film is both charming and prescient, and will seem very familiar to anyone reading about a world without work. The best scene features a virtuoso feat of associative memory showing the sheer brilliance of the character played by Katharine Hepburn (winning Tracy’s heart in the process), a brilliance the primitive electronic brain would have no chance of emulating. The movie ends with a literal deus ex machina where a machine accidentally prints pink slips to fire the entire company, only to get shut down due to its rogue disruption on operations.

The Desk Set scene where Katharine Hepburn shows a robot is no match for her intelligence.

Desk Set can teach us a lesson. The 1950s saw the rise of energy around AI. In 1952, Claude Shannon introduced Theseus, his maze-solving mouse (an amazing feat in design). In 1957, Frank Rosenblatt built his Mark I Perceptron–the grandfather of today’s neural networks. In 1958, H.P. Luhn wrote an awesome paper about business intelligence that describes an information management system we’re still working to make possible today.  And in 1959, Arthur Samuel coined the term machine learning upon release of his checkers-playing program in 1959 (Tom Mitchell has my favorite contemporary manifesto on what machine learning is and means). The world was buzzing with excitement. Society was to be totally transformed. Work would end, or at least fundamentally change to feature collaboration with intelligent machines.

This didn’t happen. We hit an AI winter. Deep learning was ridiculed as useless. Technology went on to change how we work and live, but not as the AI luminaries in the 1950s imagined. Many new jobs were formed, and no one in 1950 imagined a Bay Area full of silicon transistors, and, later, adolescent engineers making millions off mobile apps. No one imagined Mark Zuckerberg. No one imagined Peter Thiel.

We need to ask different questions and address different people and process challenges to make AI work in the enterprise. I’ve seen the capabilities of over 100 large enterprises over the past two years, and can tell you we have a long way to go before smart machines outright replace people. AI products, based on data and statistics, produce probabilistic outputs whose accuracy and performance improve with exposure to more data over time. As Amos Tversky says, “man is a deterministic device thrown into a probabilistic universe.” People mistake correlation for cause. They prefer deterministic, clear instructions to uncertainties and confidence rates (I adore the first few paragraphs of this article, where Obama throws his hands up in despair after being briefed on the likely location of Osama bin Laden in 2011). Law firm risk departments, as Intapp CEO John Hall and I recently discussed, struggle immensely to break the conditioning of painstaking review to identify a conflict or potential piece of evidence, habits that must be broken to take advantage of the efficiencies AI can provide (Maura Grossman and Gordon Cormack have spent years marshaling evidence to show humans are not as thorough as they think, especially with the large volumes of electronic information we process today).

The moral of the story is, before we start pontificating about the end of work, we should start thinking about how to update our workforce mental habits to get comfortable with probabilities and statistics. This requires training. It requires that senior management make decisions about their risk tolerance for uncertainty. It requires that management decide where transparency is required (situations where we know why the algorithm gave the answer it did, as in consumer credit) and where accuracy and speed are more important (as in self-driving cars, where it’s critical to make the right decision to save lives, and less important that we know why that decision was made). It requires an art of figuring out where to put a human in the loop to bootstrap the data required for future automation. It requires a lot of work, and is creating new consulting and product management jobs to address the new AI workplace.

Distraction 2: Universal Basic Income

Universal basic income (UBI), a government program where everyone, at every income level in society, receives the same stipend of money on a regular basis (Andy Stern, author of Raising the Floor, suggests $1,000 per month per US citizen), is a corollary of the world without work. UBI is interesting because it unites libertarians (be they technocrats in Silicon Valley or hyper-conservatives like Charles Murray, who envisions a Jeffersonian ideal of neighbors supporting neighbors with autonomy and dignity) with socialist progressives (Andy Stern is a true man of the people, who lead the Service Employee International Union for years). UBI is attracting attention from futurists like Peter Diamandis because they see it as a possible source of income in the impending world without work.

UBI is a distraction from a much more profound economic problem being created by our current global, technology-driven economy: income inequality. We all know this is the root cause of Trumpism, Brexit, and many of the other nationalist, regressive political movements at play across the world today. It is critical we address it. It’s not simple, as it involves a complex interplay of globalization, technology, government programs, education, the stigma of vocational schools in the US, etc. In the Seventh Sense, Joshua Cooper Ramo does a decent job explaining how network infrastructure leads to polarizing effects, concentrating massive power in the hands of a few (Google, Facebook, Amazon, Uber) and distributing micro power and expression to the many (the millions connected on these platforms). As does Nicholas Bloom in this HBR article about corporations in the age of inequality. The economic consequences of our networked world can be dire, and must be checked by thinking and approaches that did not exist in the 20th century. Returning to mercantilism and protectionism is not a solution. It’s a salve that can only lead to violence.

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This figure, courtesy of Branko Milanovic, shows cumulative income growth between 1988 and 2008 at various percentiles of global income distribution. Incomes for the poor steadily rise, incomes of the rich sharply rise, and incomes of the middle class decline. 


That said, one argument for UBI my heart cannot help but accept is that it can restore dignity and opportunity for the poor. Imagine if every day you had to wait in lines at the DMV or burn under the alienating fluorescence of airport security. Imagine if, to eat, you had to wait in lines at food pantries, and could only afford unhealthy food that promotes obesity and diabetes. Imagine how much time you would waste, and how that time could be spent to learn a new skill or create a new idea! The 2016 film I, Daniel Blake is a must see. It’s one of those movies that brings tears to my eyes just thinking of it. You watch a kind, hard-working, honest man go through the ringer of a bureaucratic system, pushed to the limits of his dignity before he eventually rebels. While UBI is not the answer, we all have a moral obligation, today, to empathize with those who might not share our political views because they are scared, and want a better life. They too have truths to tell.

Distraction 3: Conversational Interfaces

Just about everyone can talk; very few people have something truly meaningful and interesting to say.

The same holds for chatbots, or software systems whose front end is designed to engage with an end user as if it were another human in conversation. Conversational AI is extremely popular these days for customer service workflows (a next-generation version of recorded options menus for airline, insurance, banking, or utilities companies) or even booking appointments at the hair salon or yoga studio. The principles behind conversational AI are great: they make technology more friendly, enable technophobes like my grandmother to benefit from internet services as she shouts requests to her Amazon Alexa, and promise immense efficiencies for businesses that serve large consumer bases by automating and improving customer service (which, contrary to my first point about the end of work, will likely impact service departments significantly).

The problem, however, is that entrepreneurs seeking the next sexy AI product (or heads of innovation in large enterprises pressed to find a trojan horse AI application to satisfy their boss and secure future budget) get so caught up in the excitement of building a smart bot that they forget that being able to talk doesn’t mean you have anything useful or intelligent to say. Indeed, at Fast Forward Labs, we’ve encountered many startups so excited by the promise of conversational AI that they neglect the less sexy but incontrovertibly more important backend work of building the intelligence that powers a useful front end experience. This work includes collecting, cleaning, processing, and storing data that can be used to train the bot. Scoping and understanding the domain of questions you’d like to have your bot answer (booking appointments, for example, is a good domain because it’s effectively a structured data problem: date, time, place, hair stylist, etc.). Building out recommendation algorithms to align service to customer if needed. Designing for privacy. Building out workflow capabilities to escalate to a human in the case of confusion or route for future service fulfillment. Etc…

The more general point I’m making with this example is that AI is not magic. These systems are still early in their development and adoption, and very few off the shelf capabilities exist. In an early adopter phase, we’re still experimenting, still figuring out bespoke solutions on particular data sets, still restricting scope so we can build something useful that may not be nearly as exciting as our imagination desires. When she gives talks about the power of data, my colleague Hilary Mason frequently references Google Maps as a paradigmatic data product. Why? Because it’s boring! The front end is meticulously designed to provide a useful, simple service, hiding the immense complexity and hard work that powers the application behind the scenes. Conversation and language are not always the best way to present information: the best AI applications will come from designers who use judgment to interweave text, speech, image, and navigation through keys and buttons.

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The boring yet awesome UX/UI of Google Maps. Gideon Lewis-Kraus astutely recognizes this application would seem amazing to someone from the 1970s!

Distraction 4: Existential Risk

Enlightenment is man’s emergence from his self-imposed nonage. Nonage is the inability to use one’s own understanding without another’s guidance. This nonage is self-imposed if its cause lies not in lack of understanding but in indecision and lack of courage to use one’s own mind without another’s guidance. Dare to know! (Sapere aude.) “Have the courage to use your own understanding,” is therefore the motto of the enlightenment.

This is the first paragraph of Emmanuel Kant’s 1784 essay Answering the Question: What is Enlightenment? (It’s short, and very well worth the read.) I cite it because contemporary discourse about AI becoming an existential threat reminds me of a regression back to the Middle Ages, where Thomas Aquinas and Wilhelm von Ockham presented arguments on the basis of priority authority: “This is true because Aristotle once said that…” Descartes, Luther, Diderot, Galileo, and the other powerhouses of the Enlightenment thought this was rubbish and led to all sorts of confusion. They toppled the old guard and placed authority in the individual, each and every one of us born with the same rational capabilities to build arguments and arrive at conclusions.

Such radical self reliance has waxed and waned throughout history, the Enlightenment offset by the pulsing passion of Romanticism, only to be resurrected in the more atavistic rationality of Thoreau or Emerson. It seems that the current pace of change in technology and society is tipping the scales back towards dependence and guidance. It’s so damn hard to keep up with everything that we can’t help but relinquish judgment to the experts. Which means, if Bill Gates, Stephen Hawking, and Elon Musk, the priests of engineering, science, and ruthless entrepreneurship, all think that AI is a threat to the human race, then we mere mortals may as well bow down to their authority. Paternalistic, they must know more than we.

The problem here is that the chicken-little logic espoused by the likes of Nick Bostrom–where we must prepare for the worst of all possible outcomes–distracts us from the real social issues AI is already exacerbating. These real issues are akin to former debates about affirmative action, where certain classes, races, and identities receive preferential treatment and opportunity to the detriment and exclusion of others. An alternative approach to the ethics of AI, however, is quickly gaining traction. The Fairness, Accountability, and Transparency in Machine Learning movement focuses not on rogue machines going amok (another old idea, this time from Goethe’s 1797 poem The Sorcerer’s Apprentice), but on understanding how algorithms perpetuate and amplify existing social biases and doing something to change that.

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An 1882 illustration of Goethe’s Sorcerer’s Apprentice, which also dealt with technology exceeding our powers to control it. 

There’s strong literature focused on the practical ethics of AI. A current Fast Forward Labs intern just published a post about a tool called FairML, which he used to examine implicit racial bias in criminal sentencing algorithms. Cathy O’Neill regularly writes articles about the evils of technology for Bloomberg (her rhetoric can be very strong, and risks alienating technologists or stymying buy in from pragmatic moderates). Gideon Mann, who leads data science for Bloomberg, is working on a Hippocratic oath for data scientists. Blaise Agüera y Arcas and his team at Google are constantly examining and correcting for potential bias creeping into their algorithms. Clare Corthell is mobilizing practitioners in San Francisco to discuss and develop ethical data science practices. The list goes on.

Designing ethical algorithms will be a marathon, not a sprint. Executive leadership at large enterprise organizations are just wrapping their heads around the financial potential of AI. Ethics is not their first concern. I predict the dynamics will resemble those in information security, where fear of a tarred reputation spurs corporations to act. It will be interesting to see how it all plays out.

Distraction 5: Personhood

The language used to talk about AI and the design efforts made to make AI feel human and real invite anthropomorphism. Last November, I spoke on a panel at a conference Google’s Artists and Machine Intelligence group hosted in Paris. It was a unique event because it brought together highly technical engineers and highly non-technical artists, which was a wonderful staging ground to see how people who don’t work in machine learning understand, interpret, and respond to the language and metaphors engineers use to describe the vectors and linear algebra powering machines. Sometimes this is productive: artists like Ross Goodwin and Kyle McDonald deliberately play with the idea of relinquishing autonomy over to a machine, liberating the human artist from the burden of choice and control, and opening the potential for serendipity as a network shuffles the traces of prior human work to create something radical, strange, and new. Sometimes this is not productive: one participant, upon learning that Deep Dream is actually an effort to interpret the black box impenetrability of neural networks, asked if AI might usher a new wave of Freudian psychoanalysis. (This stuff tries my patience.) It’s up for debate whether artists can derive more creativity from viewing an AI as an autonomous partner or an instrument whose pegs can be tuned like the strings of a guitar to change the outcome of the performance. I think both means of understanding the technology are valid, but ultimately produce different results.

The general point here is that how we speak about AI changes what we think it is and what we think it can or can’t do. Our tendencies to anthropomorphize what are only matrices multiplying numbers as determined by some function is worthy of wonder. But I can’t help but furrow my brow when I read about robots having rights like humans and animals. This would all be fine if it were only the path to consumer adoption, but these ideas of personhood may have legal consequences for consumer privacy rights. For example, courts are currently assessing whether the police have the right to information about a potential murder collected from Amazon Echo (privacy precedent here comes from Katz v. United States, the grandfather case in adapting the Fourth Amendment to our new digital age).

Joanna Bryson at the University of Bath and Princeton (following S. M. Solaiman) has proposed one of the more interesting explanations for why it doesn’t make sense to imbue AI with personhood: “AI cannot be a legal person because suffering in well-designed AI is incoherent.” Suffering, says Bryson, is integral to our intelligence as social species. The crux of her argument is that we humans understand ourselves not as discrete monads or brains in a vat, but as essentially and intrinsically intertwined with other humans around us. We play by social rules, and avoid behaviors that lead to ostracism and alienation from the groups we are part of. We can construct what appears to be an empathetic response in robots, but we cannot construct a self-conscious, self-aware being who exercises choice and autonomy to pursue reward and recognition, and avoid suffering (perhaps reinforcement learning can get us there: I’m open to be convinced otherwise). This argument goes much deeper than business articles arguing that work requiring emotional intelligence (sales, customer relationships, nursing, education, etc.) will be more valued than quantitive and repetitive work in the future. It’s an incredibly exciting lens through which to understand our own morality and psychology.


As mentioned at the beginning of this post, collective fictions are the driving force of group alignment and activity. They are powerful, beautiful, the stuff of passion and motivation and awe. The fictions we create about the potential of AI may just be the catalyst to drive real impact throughout society. That’s nothing short of amazing, as long as we can step back and make sure we don’t forgot the hard work required to realize these visions, and the risks we have to address along the way.


Sam Harris and a16z recently interviewed Harari on their podcasts. Both of these podcasts are consistently excellent.

**One of my favorite professors at Stanford, Russell Berman, argued something similar in Fiction Sets You Free. Berman focuses more on the liberating power to use fiction to imagine a world and political situation different from the present conditions. His book also comments of the unique historicity of fiction, where works at different period refer back to precedents and influencers from the past.