The GUIey Middle of Artificial Intelligence

The basic premise of artificial intelligence, to use enormous amounts of data to find out new things, is easy to grasp. If any one of us had the time and stamina to study a million photos or stories about a thing, I’m sure we’d come up with insights about it too. 

Business products emerging from current applications of artificial intelligence are also logical and simple to get your head around. Smart thermostats sell because they are convenient and deliver energy savings. Marketing approaches that analyze shopping patterns to suggest items people are likely to buy are winners in retail for their potential to increase sales.

How does AI get from data analysis to creating desirable products? In diagram version, this seems to me:

A few hypothetical1examples:

1. Using AI to improve diagnosis of medical images. Input: One hundred thousand pathology slides of renal cancer and one hundred thousand slides of normal kidney tissue. Outcome: Improved differentiation between normal and malignant kidney biopsies. Doctors win because the accuracy of diagnosis increases, saving healthcare costs by prescribing the right treatment for patients. Patients win because they are either can carry on their lives disease-free or have greater certainty in the treatment they need.

Mysterious GUIey2inside: What is the AI looking at to distinguish between normal and cancerous cells in pathology slides?

2. Using AI to improve traffic flow. Input: Every car in the city communicates its starting point, destination, and real time location to a central database. The goal is to send a uniform volume of traffic via every available route so that none are over-used or under-used. The outcome is a clear win – optimum travel efficiency for everyone, saving time, auto costs and impact to the environment by decreasing energy consumption.

Mysterious inside: What is AI doing to manage all the permutations and combinations to direct even traffic flow?

The two examples are different. In the first one, the criteria AI uses to distinguish between normal and malignant cells are the mystery. Pathologists could list the traits they use to make a decision when looking down a microscope, but is AI using the same ones? In the second, it’s the speed and capacity to deal with volumes of users that’s amazing. It’s not difficult to suggest the best route for your mother to take home, based on knowledge of traffic patterns at the time of day in your home town, but who could do that for 3 million occupants of a city simultaneously?

I’ve read that we are unlikely to be able to extract the GUIey middle3from AI supported processes, due to the iterative nature of the learning. When a person really understands what they are doing, they can explain it. If a chef tells you their sumptuous meal resulted from ‘a little of this, a little of that’, they likely know exactly what went into the dish, but aren’t telling to protect their trade secrets. If my mechanic tells me they are basing the diagnosis of what’s wrong with my car on some data from other cars but doesn’t know which models or what kind of data, I’m looking for another mechanic.

Is not knowing how AI works any different than not knowing the detailed working of automobiles, or any other complex object or process in modern life – elevators, mortgage documents, dental implants? The fundamentals of the car I get – the energy of exploding fossil fuel is converted into angular momentum that torques the axels and moves me, in my steel and plastic carriage, to where I want to go. The business model is also easy – the speed and convenience of reaching destinations in relative comfort with the added efficiency of carting a group of people, sheets of drywall, or my dogs with me. There is someone who can explain ABS brakes, how the muffler is connected to the engine, and all the other components that make a car function. With AI, either by design or trade secret, the explanation is hidden.

We need to know the mysterious processes that AI systems use to derive new knowledge from the volumes of data consumed. Forget proprietary algorithms. This is brave new territory we are entering and transparency is important so we can be sure we are operating safely and ethically.4

History is full of examples of embracing new things without a full understanding of the implications5. From that, a machine would learn that we need to know how things work before we can use them safely.

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1Both of my examples are likely to be real enterprises but staying hypothetical is better for this discussion.

2This is a pun on GUI type computer interfaces, which use icons, rather than typed commands, to tell computers what to do. GUIs make programming simpler. I’m suggesting by making things simpler with AI, we are making them less transparent, dissectable or amendable to understanding how the parts work together to create the whole. Less concrete. More gooey. Gooey-er. Soft and flowing, changing shape easily.

3I do know that the process AI uses is a very large series of logic functions, of the sort: if X does Y, then A is the outcome. If X, K and J, do B, then L is likely to happen. If X does Y but K does something else, and it’s Tuesday, then Blue is the right answer. Etc. Oh, and the AI may start with a bunch of logic statements but change them on the fly as more data comes in or if in testing a hypothesis, it doesn’t deliver satisfactory answers.

4For many examples, read ‘Weapons of Math Destruction’ by Cathy O’Neil

5A few examples that spring to mind – nuclear weapons, cigarettes, social media, plastic, many types of home insulation, lead paint, breeding of dogs, trans-fats, mortgage backed securities.

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Destructive Creative Destruction


You know the list. The technologies, labelled creative destruction, that changed life as we humans knew it: Fire. Pasteurization. The assembly line. Washing machines. Email. Mobile Phones. 

Each of these had a dramatic impact on society, generally decreasing the effort required to do a vital human activity and allowing us to do other, more interesting things1.

Should plastic be added to the list?2 When introduced, it was a major new technology and found broad applications3. The ability to engineer polymers so they are flexible, solid, durable, the right colour and shape, mass-producible, light-weight and low cost lead to the introduction of many new products. Products like plastic bags, straws, packaging. The coating on electrical wires. Cheaper just about anything: shoes, suitcases, light fixtures, flooring, automobile components, toys, machine parts, human body part implants. The list goes on forever.

What has been disrupted by plastic?

Most things plastic are affordable, leading to increased consumption of each item. They tend to be single use, by which I mean two things: disposable or non-repairable. Disposable comes from the low cost – “I’m tossing this out because I can get another one for 3 cents”. Non-repairable because of the process used to create plastic widgets. Stuff made out of other substances known to humans can be engineered and modified. Wood, metal, cement, kryptonite4, plaster can all be fiddled with and/or repaired. Plastic, not so much. To be fair, this is what makes plastic appealing – the ability to spin or mold or extrude it into different shapes. The consequence is that it can’t be fixed because it’s all one piece.

Back to disruption. Here’s some of the ways plastic has changed in our lives:

  • Eating on the run. Plastic containers, plates and utensils made it possible to grab a meal from the takeout window or mall kiosk and eat it anywhere, rather than tethering dining to a venue that could manage ceramic plates and metal forks. 
  • Because plastic changed packaging, it facilitated transportation of goods to distant locations. Thus, more competition in many markets. Lower prices. More choice for consumers.
  • Plastics made many things affordable to more people. Furniture. Cars. Etc. A new social order of ownership emerged.
  • Not coincidentally, with the rise of plastic goods came the era of consumption. Affordable stuff enabled (and required – see above about repairing plastic items) frequent replacement of the items.

Many substitutes, such as plastic bags for paper bags, plastic bumpers on cars, plasticized paper cartons for milk rather than glass bottles, may seem disruptive, especially to the producers of paper bags, metal bumpers and glass milk bottles, but don’t actually result in a new social order.

From my list, plastic has disrupted: sit-down meals, local sourcing of goods, possessions as symbols of wealth, and the need for expertise in repairing many things. Based on fundamental values of community and social connectedness, as well as environmental stewardship, I’d say three of the four of these aren’t good. It could be argued that disrupting possessions as symbols of wealth, is social advancement. Otherwise, plastic disruption has not been good to us, even thought there are plenty of benefits to the use of plastic.

This disruptive technology (generally considered a good thing as it ushers in a new approach to old problems, makes life easier and richer) had negative consequences.

The earth has a problem with plastic. It doesn’t decay, ever. Even kryptonite decays. Plastic was celebrated for its disposableness, while ironically its permanence has clogging up the landfill, oceans, and microcirculation of the earth’s creatures. Oops, we created a monster. Vacuous consumerism snowballs the problem of overflowing landfill, making the monster multi-headed, with enormous tentacles and an awful smell.

Sometimes, what seems like a good idea at the time isn’t. Plastic isn’t the first time the true impact of a novel product wasn’t realized until time and mass consumption had gone by. Cigarette smoking. Fossil fuel emissions. Drugs with fatal side effects in one-in-a-million patients.

Fortunately, the plastic pollution crisis presents all kinds of opportunities for new creative destruction. Constructive creative destruction, please.

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1Fire allowed us to cook food and stay warm, increasing survival. Pasteurization was a process that made milk and other foods safer and allowed them to be transported further, increasing both the availability of food and the livelihood of producer. After the invention of the assembly line, cars became more accessible to different socio-economic groups and then expanded their horizons. Washing machines and other appliances are credited with allowing women the ability to lead a life outside the house, as it became possible to spend less than all of their time doing household chores. I don’t have to explain how email and mobile phones have changed the way we communicate, but future generations will need to be told.

2It piqued my interest when I saw it on a list of disruptive technologies in ‘Prediction Machines. The Simple Economics of Artificial Intelligence’ by Ajay Agrawal, Joshua Gans and Avi Goldfarb, so thanks to them for making me think.

3For a great summary of the history of plastic, I recommend this https://www.sciencehistory.org/the-history-and-future-of-plastics

4Kidding, kryptonite isn’t on the list, it isn’t real.

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The Entrepreneur as Customer

“I’m going to live to be 1401,” I often say. 

People laugh, which is fine. I am serious.

“But I’m going to need replacement parts,” I usually add.

Thus begins my adventure as a customer in an emerging industry: regenerative medicine. Interesting to experience entrepreneurship from the buy-side. In IT entrepreneurial circles, this happens all the time. Early adopters of new technology come from within the industry, as they are in a position to understand the need and the benefits of innovations before a broader population.

I understand first-hand (pun intended) the basic human need for tissue regeneration – it literally relieves the pain caused by degeneration. After years of wear and tear, the cartilage my CMC joint2is almost gone and won’t heal. Delicate grasping is painful – I drop things. This inability to hold a piece of paper may impede my journey to the 22ndcentury3.

I’m faced with the intractable. Modern medicine has no restorative solutions. There are pain killers. Supportive braces. Electric can openers. It’s a problem that should be remedied, not compensated for.

There is an experimental approach: Stem cells. The scientist in me understands the theory, knows it could be the ultimate answer. Soft tissue replacement parts could be made – by installing a biological factory that regenerates the lost bits. But it’s new technology with limited testing, testing that might provide surprises not covered by the theory.

I leapt at the opportunity to undergo a cell transplant procedure with a full understanding of the risks, uncertainty and cost.

The trigger event for the this new technology were findings4that fat cells, from the abdomen, are a source of stem cells – cells that have the potential to multiply and form various types of tissue. This source is appealing (competitive advantage), compared to alternatives, that are uncomfortable for the patient (bone marrow harvest), or carry risks of rejection (if the stem cells are from a third party donor, rather than the recipient) or selection of unwanted features (culturing the cells in between harvest and injection may amplify unwanted traits). Hip and knee joint replacement is common with metal, plastic or ceramic parts. While generally successful, it is major surgery, costs $10,000’s, and requires months for the patient to fully recover. Replacement joints are less common in the hands.

I am an early adopter. Perhaps a consumer of an early stage prototype or minimum viable product, provider of input to get to product/market fit. Maybe even an investor, although I want to know if this is a scalable product. Currently, it needs a surgeon for administration, and a bunch of surgical equipment. However, this is indeed what puts the technology at the stage of product/market fit. It isn’t clear that the current approach can meet mass market demand, for technical reasons as much as anything else.

There is a great opportunity here. Clear unresolved pain, competitive advantage, timeliness, and a massive market for an effective treatment of osteoarthritis. The Arthritis Foundation states that 31 million Americans have osteoarthritis, and the expectation is that this will reach 78 million by 2040.5That’s a 5% year/year growth rate sustained for 20 years in a whomping big market. 

I’m excited to see the outcome of my treatment. Will there be regeneration and healing, so I can do mundane things like open a chip bag or put on socks without pain? There are no guarantees. As an emerging technology, there is knowledge to accumulate to optimize the product, possibly making it more effective and reliable. I’ll take the risk. I’m thrilled to be part of the development of this technology, the possibility to make a difference. That’s what entrepreneurship is all about.

——–

1I came up with this number after reading a theoretical paper many years ago about the limits of the human life span. Current estimates range from just over 100 to no limit. 

2Where the thumb bone connects to the wrist bone.

3This may seem melodramatic but there are studies that link an inability to do minor tasks with increases in depression, obesity and other chronic illness. 

4This paper summarizes the findings of a number of studies: Miana, V. V., & González, E. (2018). Adipose tissue stem cells in regenerative medicine. Ecancermedicalscience12, 822. doi:10.3332/ecancer.2018.822

5https://www.arthritis.org/about-arthritis/understanding-arthritis/arthritis-statistics-facts.php

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A Scientific Approach in Entrepreneurship and Strategy

Thinking like a scientist. This may not be new, especially for scientists. And not so much for entrepreneurs who subscribe to Eric Ries’ Lean Startup method1. But it was a hot topic at the recent Academy of Management (AOM) conference.2

I’m a scientist who has lived in the business world for decades. So, I’m excited to see the scientific method embraced at a business-centred conference. The AOM is an organization of business scholars, or people who study business. However, like every business school I’ve been part of, AOM aims to share knowledge with the practicing community.

First observation: Transparent Logic. The term immediately resonated – I knew exactly what it meant and why it was important in entrepreneurship. Transparent logic is part of a model for teaching social entrepreneurship3 and requires a clear link between the proposed activities and the social problem a venture is tackling. For example, providing water purification devices will decrease the incidence of dysentery, leading to fewer hours of lost labour and therefore people earning a better wage, however, it needs to be clear how people who need the device will get them and continue to use them. For many scientists, cause and effect is utopia. Transparent logic in a social venture seeks this holy grail of cause and effect.

At a session on entrepreneurial strategy4, we heard it was less about SWOT analysis and more about observation leading to hypothesis generation. An entrepreneur sees an unsolved problem and hypothesizes they can solve it with a certain product. The term causal logic came up, followed rapidly by notions of testing. Establishing value, after recognizing opportunities, can have its roots in the scientific method. The entrepreneurial process is scientific.

In the same session, a trial to evaluate the impact of the scientific method on startups was presented. Entrepreneurs were randomized into two groups. One was mentored traditionally – entrepreneurs were guided in business methods, product development and organizational development. The other group was tutored in a scientific method, using hypothesis generation, controlled testing and analytical methods to learn from test outcomes. Those using the scientific method pivoted more frequently, acquired and activated more customers and had more revenue generation. From this: the scientific method works for entrepreneurs.

On to a plenary session on strategy.5 There, too, causal identification was presented as a frontier in strategy research. My head started to spin with so many scientific references. I was brought back to objectivity, reminded that physics with its fundamental, timeless certainties such as gravity, was more reliable for test outcomes. The fundamental forces that shape business shift more often. However, like evolution of species, changes in strategic theme occur in leaps and bounds, rather than continuously. An example is the upheaval in retail, with the onset of online shopping. A discrete change in how we shop. It left survivors (Amazon) and the less fortunate (Sears Canada).

The hotness of the scientific method in business strategy looks to me like the mid-point stage on the S-curve6 of adoption of new things (technology, products, buzz-words, sports teams). Following this trajectory, soon it won’t be the new thing, but the common thing.

When I ventured out of the lab many years ago to join an investment bank, I was a foreigner. Welcomed, but in a world of people who thought in different ways. They had vision. Visions of logical explanations. Maybe it’s me that’s catching up, learning that shrewd entrepreneurs see value where other’s don’t.

The scientific method can make sense and compelling arguments out of ideas. It makes it easy to answer hard questions about why you think this new idea you have will make a great business. A great tool for any entrepreneurial business strategist.

——–

1http://theleanstartup.com

2This is a huge conference, attended by thousands of faculty members from business schools all over the world. With two days of symposia, plenary sessions and papers, each with 7 time slots, and an average of 15 sessions to choose from per time slot, this means there are (15) 14 = 2.9 x 1016 different individual selections of talks to attend. Or maybe it should be 15! which is only 1.3x 1012 I’m not exactly sure how to calculate the number of different permutations of the program but any way you do, the number is really big. So my experience may not be typical.

6Not surprisingly, the S curve is S shaped.

In the beginning, a handful people embrace a new thing. The adventurers, the risk-takers, perhaps those in the field who understand the new thing better than most. This is the first stage, the flattish bottom to the S curve.

Then word starts to get around. The new thing is good. It does exciting things. It’s better than the old thing. People jump on board, start adopting the new thing like it’s the best thing since the last new thing. This is the part of the curve that swings up so rapidly that if it was an airplane, everyone on board would pass out.

As time goes on, people remain excited about the new thing, but many people have the new thing, so the adoption curve starts to lessen its assent – the plateauing phase of the vertical rise.

Finally, just about everyone who will ever want the new thing, which isn’t so new any more, has it. The S curve flattens. No additional adoption because everyone loves and appreciates the new thing.

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AI Personal Assistants – The Death of Shopping as we Know it

Predictions are, in the near future, we will each have a personal assistant with artificial intelligence (AI)1 that runs our life. It’ll order household items before we run out, book social engagements, reminds us of upcoming events and related purchases (like birthday gifts, a bottle of wine for the hostess, or a new outfit to wear to the party).

More elaborate predictions have the AI constantly searching for better deals on services like vehicle sharing, archery lessons or landscaping services. It’ll sample the news wire for updates on unhealthy foods or ethically produced music, keep up to date with product reviews (posted by other people’s AI personal assistants) and use this collected wisdom to amend our purchase decisions (which the AI made in the first place, so we won’t even know).

This got me to imagining the end of marketing as we know it. No more emotional buying decisions. Every single purchase would be made with the maximum amount of data and, hopefully, solid facts.

Why would an AI be interested in brand loyalty? An AI would access all available information to determine if the latest version of a brand name item delivered on the quality expected, and if not, find another brand that did. Far fewer buying decisions would be based on the logic ‘I’m buying Apple because Apple makes good technology’. Your AI would buy Apple if there was proof it was the best available technology. And the proof would come from objective tests and the unbiased reports of AI’s everywhere (because why would an AI lie?).

Trickier is image, prestige, lifestyle or that thing where you buy a certain brand because it reflects who you want to be. Would your AI get that, have the same image of you as you do? That you wear a certain type of sneaker because people who share your values do.

Then there’s the ability to forget things you prefer to forget. Like booking a dentist appointment because you don’t like going to the dentist, so putting it off another month would be fine. Would your handy personal assistant let you do that? The dentist would be happy if you came back more often, so the dentist’s AI would encourage yours to book, maybe offer a discount. The same rationale could apply for the vet, furnace cleaning, arranging a visit to those relatives you find tedious, getting the oil changed in the car you jointly own, and a few dozen other things that fall into the category of adulting ( willingly doing things you know are good for you but are unpleasant, no fun, boring etc).

Then there’s retail therapy. Could your AI pick out the perfect new sweater for you, when you don’t need a new sweater and can’t afford it, but accidentally yelled at your boss, spilled milk on your toddler, and got a ticket for not going through a green light all in one day?

Is having an excuse to get out of the house a thing any more? Shopping used to be a good neutral destination that always worked if you needed something to do or to get away from the humans you lived with. You can’t get your AI to do that for you. Unless it pretends to be your friend who has to meet you at the mall.2

There will always be new ways of doing things. But humans are humans. We learned to live much of our life online, but we shop for more reasons than to get stuff. We also forget things on purpose. We act on our emotions because that’s what makes us human.

I think I’ll sneak out of the house, tell my AI personal assistant I’m on my way to the dentist, then cancel the appointment so I can go shop for stuff I don’t need, but want.

——-

1Purchased from a large tech company and embodied as a hockey puck-size matt silver thing that sits on the kitchen counter.

2If this sentence doesn’t make sense to you, please review a TV show or movie from the 1970’s for context.

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Barriers to Innovation

My last post was an optimistic ode to the endless innovation currently possible, due to the state of technology, entrepreneurship and related support systems. But that doesn’t mean it’s easy. Today, I want to discuss some sobering limitations that thwart the introduction and uptake of new things.

Several broad categories of barriers to innovation spring to mind:

  • regulation
  • fitting into existing infrastructure
  • consumer habits
  • figuring out who is going to pay
  • short term vs long term thinking
  • benefit twice removed

To illustrate these, I’ll discuss barriers in a couple of hypothetical situations where delivering a solution seems easy.

Consider the challenges to providing real-time transit information. This was inspired by a comment I overheard: “in X,Y and Z city, you know exactly when the next bus will arrive; why can’t we have that here?”

Why indeed?

The technology exists to track a vehicle, create algorithms to integrate the traffic flow, rate of bus progress, passenger demand and weather conditions to estimate and adjust time of arrival for buses and trains. Multiple options exists for providing this information to transit customers, such as pixel boards at stops, a downloadable app or text message service. The information is useful to customers to plan their commutes and use their time wisely. Providing real time updates enhances the customer experience, because it’s more satisfying knowing that your bus will arrive in 14 minutes than not knowing and having it appear after you have fretted and peered into the traffic for 6 (much longer) minutes. Happier customers are repeat customers. So, there’s value to be shared between provider and customer.

Why can’t they have it everywhere?

I can think of a bunch of (hypothetical) reasons.

1. Perhaps the current fleet of vehicles aren’t GPS enabled. Perhaps there is no way of announcing the information at the stops, since all that currently exists are metal signs. (infrastructure issues)

2. The bus drivers union may object to such a system because it tracks driver performance in an unfair way. Or the legal team could be concerned about liability of promising something not under the control of the transit authority. (regulations)

3. How will the new infrastructure be paid for? Through fare increases, increased bank loans, or decreased dividends to shareholders? Although the value can be seen, is it enough to make people reach into their pockets? (who will pay?)

4. The cost to implement this new system will have to be paid long before rider retention can be proven. (short term vs. long term thinking).

To illustrate the other two barriers, I’ll use plastic utensils, especially straws. Much has been made of the earth- and ocean-clogging features of these implements of consumption lately. We need an alternative. Why do we use straws to consume beverages? (This is customer habit.) Innovations that replace the straw must overcome habit. And why do we have plastic utensils, food containers and other disposable, polluting conveniences? Because they are convenient. Eating your meal and cleaning up afterwards are things you will enjoy right now. Pollution of the oceans may only come to your attention years later. And you’re not sure how plastic in the waters effects the environment. It’s difficult to understand the vastness of the consequences of disposables in the sea when you put a single straw in your bubble tea. (benefit twice removed)

Yes, there can be significant barriers to implementing a genius idea that is good for people, business and society as a whole.

And yet, the answer is innovation. Business innovation. Get around the regulations or change them. Show stakeholders short and long term benefits. If there is value in an innovation, someone will be willing to pay. People only cling to their habits if they don’t see the benefit of changing.

Innovation is possible, if you understand the barriers and come up with ways to get over, under or around them.

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What’s New in Innovation?

How cool is a conference that opens with a humanoid robot (Sophia) and a hologram of her creator (Dr. David Hanson) discussing artificial intelligence?

They were okay, but the real revelation I got from this year’s OCE Discovery wasn’t flashy, revolutionary or disruptive. I wasn’t transported to a new reality. Instead, I looked around and realized: we’re here. Here, at a place where innovation has few limits.

Technology is not limiting.

Data is not limiting.

Knowledge is not limiting.

Being an entrepreneur is not limiting.

What’s left is to ask the right questions, choose the problems to tackle, the needs to fulfill.

Let me explain. First though, let me say this post tumbled out of my brain1 after listening to many inspiring presentations by David Hanson, Megan Smith, speakers in the Keynote panel on Transformative Technologies, and panels on Artificial Intelligence and Smart Cities at the 2018 OCE Discovery, an annual, award-winning innovation-commercialization conference.

Technology. There are several waves breaking onto the beach of everyday life: Artificial intelligence. Machine learning. Big data. The internet of things. Robotics. The capacity to use information is immense, because of increased transfer rates (5G), increased availability (social media, GPS) or increased monitoring (sensors on everything). It goes beyond what humans are capable of by combining the storage power of machines with the processing power of machines. Sure, there are still technical challenges, but there is capacity to write algorithms, apply principles, reduce to practice. We are on the cusp of autonomous cars, SMART homes, apps to help us do everything from planting vegetables to grocery shopping to putting out the garbage.

Data. We have reams of data. We have reams of accessible data. Accessible both because it’s been collected and because some of it is public. Our phones and search engines probably know more about us than we do ourselves. Watson, the super-intelligent computer, knows more about medical studies than doctors2. Is Shakespeare is available in Klingon or which of his plays have been performed most often? This data3 is available.

Knowledge. Don’t know how to do something you want to do? Search. If that doesn’t work, ask. See above for accessibility of technology and data. Seriously, you can learn how to do just about anything on the internet, or at least find someone to teach you. The sharing economy has not only brought us cheaper rides and accommodation, it has shifting thinking to collaboration and partnerships so people are willing to share their expertise.

Entrepreneurship is best defined by what it no longer is. Entrepreneurship is an acceptable career choice. Starting your own business is cool now, although there was a time it was considered nasty capitalism by some. While starting your own business isn’t trivial, it’s better supported in Canada than it ever has been, with incubators, accelerators, educational programs, and accessible resources. What works and what doesn’t in entrepreneurship is understood better than it was 10 years ago. Due to the technology, data availability, and knowledge sharing, developing an idea into a business has never been easier. The challenge now is how to encourage and support people to do it.

That’s what struck me. We can do any number of things. We only have to decide what we want to do. Do we need to curate traffic so here are no more jams? Should we understand weather patterns to predict umbrella demand? Can we make a difference by diagnosing a disease before it is symptomatic? How do we reduce energy consumption? Waste less. Care for more.

From the miraculous to the mundane4, we have the technology, data and knowledge. We can build it, better, stronger, faster, for less than millions of dollars.

Combining creative risk-taking (entrepreneurship) and utilization of available resources (technology, data and knowledge), we can solve an enormous number of problems.

All we need is to just do it5.

——-

1Being inspired by interesting people was even better than not realizing David Hanson was a hologram until his talk was almost over.

4 Which is which may depend on your perspective – consider bringing entire populations out of poverty with microloans or being able to recharge your phone anywhere.

5 There are barriers and challenges to developing any idea into a tangible solution but I hate to be pessimistic. The Discovery conference was uplifting. We have so much potential. In my next post, I’ll take a critical look at common barriers to solving problems.

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How Smart do you Want your Things to Be?

In the not too distant future, all things will be smart. All inanimate objects will have sensors that collect information, and artificial intelligence to analyze and react to the information.

A first generation example is motion sensors that have the sense to turn on lights when people, or your rottweiler, enter the room. Getting a little more sophisticated, there are devices like the Nest that learn from your habits and adjust the heating or a/c to create the most comfort in the most economical way. In the future (like next week), you may have a fridge that records the comings and goings of food over time and after it’s learned enough, places an order to the local food deliverer [probably Amazon] to restock all your staple foods, and suggest a few new offerings that it has calculated you might like based on your love of strawberries, mustard and corn chips. [shudder]

Everything, absolutely everything, will be smart. And helpful, in an artificially intelligent kind of way. In the spirit of embracing the future and getting the most out of it, I have a question for you:

What things do you most want to be smart and which do you least want to be smart?

Sure, I want world peace, cures for all hideous diseases, healthy, cheap food for everyone, but even AI is unlike to make those things something Amazon can deliver. And on the big picture down side, I don’t want my vacuum cleaner to take over ventilators at the hospital, the power grid to decide what temperature it should be in my home, or robots to terminate all human life because there isn’t enough calcium in the compost.

Smart stuff is likely to be more mundane in the near future (like next week and the one after that), so my expectations are lower.

Here are my smart wants:

I most want my electronic devices (which will be all things, including those we don’t consider to be electronic devices right now, like a hairbrush) to be smart enough to recognize me so I don’t have to remember 1,750 different user names and passwords. Of course, I expect perfect accuracy (the hair brush can tell the difference between me and my daughter, who likes to use it on the dog) and that they won’t let someone who has replicated my fingerprints, retinal pattern, voice or heartbeat to have access to my apps (especially my daughter, who is a likely candidate for trying to hack my stuff).

I want smart things to take away some of the pain I now have obtaining secure access to everything.

I least want something interfering in my learning process. I fiddle. I explore. I figure things out by taking a few steps and then pondering how it might work. After several rounds of this, if I complete a task I haven’t done before, I’m proud. This is how life happens for me, whether it’s setting up a website, doing home repairs or starting a company. The last thing I want is an AI chiming in to tell me how to do it at the first sign I’m stumped, or worse, 5 minutes before I realize I’m stumped.

To the average smart thing of the future, my message is: ‘if I want your help, I’ll ask for it’. What I don’t want is a smart-ass thing. A know-it-all thing. Any number of things could provide too much information. A hammer could disapprove of your the choice of nail. A pot could have opinions on the temperature applied or the nutritional content of the food it’s required to cook. Your CRM might remind you to call a particular client or that you’ve called one excessively, ignoring your personal ‘feel’ for how to deal with people.

Overall, I’d like smart things that see the difference between challenges that are annoying because they demand unnecessary attention (like where you put down your phone) but appreciate when a challenge is a good thing so you give it some thought (like understanding how to manage  privacy settings).

Of course, what annoys me may be a learning experience you want. Maybe you want instructions the second you pick up something because you’d rather spend your time watching videos. Or you’re a security buff and don’t want an AI to remember your passwords.

We’re all different, so it will take very smart things to please us all.

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Great Networking Events

Is networking a skill required by established entrepreneurs? Apparently it is1, even though many entrepreneurs consider themselves too busy doing exactly what they need to do to build their business for the random unplanness of networking.

There are zillions of blogs with advice for attendees on how to navigate the social and logistic challenges of networking. Here, I ponder what differentiates a great event from a mediocre one, inspired because I’ve discovered PitchitTO/York/Durham/etc 2. The Pitchits are 3 for 3, as far as I’m concerned. Being the analytical type, I need to dissect to find the ingredients that makes them so good.

I recommend networking to entrepreneurs for three reasons: learning, community, and building the business. Controlled serendipity is a rush. There’s magic when you bump into the person who:

1. can explain something you’ve been trying to figure out (or you’re the explainer and help someone else), [learning]

2. has the same challenges you do, [community]

3. wants to hire you to do a project you know exactly how to do [business].

Recent examples I experienced from each category:

1. On marketing. Do you find it hard to speak convincingly about your own abilities – key if you provide knowledge-based services? Someone said to me: ‘Consider it a natural ability that you should share.’ Wow! That sounded so much more palatable than pushing services. It turned ‘I’m selling this thing and I think you should buy it’ into ‘Let me help you because I know how’. [learning]

2. Sleepless nights. Even though I do a lot of speaking in front of (sometimes) critical audiences, it makes me nervous. Sometimes, so nervous I can’t sleep. Hearing someone else, a successful, public-speaking someone else, recount the same experience, only worse, gave me great comfort that even when it looks easy, it isn’t. [community]

3. Clients. Yes, I’ve found clients at networking events. [business]

A good networking event makes it easy for every attendee to find people to learn from, share with, and do business with. And this happens how? I won’t pretend to have the perfect recipe, but can make a few observations based on years of attending everything from the dullest events where no one moved from their front-of-the-room-facing seats, to ones that were so high energy I needed several hours to calm down afterward.

Here’s what I think makes a good event:

  1. The right physical space. Find an interesting, quirky setting. Maybe it has natural beauty, sunlight, water, or a forbidden quality. Make it somewhere people feel good. If they have to sit down, have them do it at large tables. Small ones form hard-to-enter cliques. Treat the attendees like house guests. Give them food, drink, bacon even.
  2. Invite well. We all know the marketing rules about reaching the right audience – publicize to find unconnected but like-minded people and those with a breadth of experience from seasoned to fresh out of school. Stack the deck of attendees with people you know will mingle and be inclusive. It’s a numbers thing3 – if enough of the attendees are determined to talk to everyone, then everyone will talk to everyone.
  3. Awesome leadership. It works in large corporations and small, and networking events. Good leadership – vision, coaching and walking the talk, will set the tone. The message should be loud and clear that everyone is there to help each other and learn from each other and do business together (see above three principles).
  4. The Program. Putting effort into crafting a stimulating program will get people talking. Inciting excitement gets the room riled up and ready to chatter.
  5. Fun. The culmination of all of the above, the atmosphere, the attendees, the leadership, and the event schedule, should be fun – enjoying life while making things happen.

Finding networking events that deliver all these things won’t happen all the time. And there is an element of personal fit. Not every venue, topic, or style energizes everyone in the same way. My latest find – the Pitchit events – have all the right elements – atmosphere, appropriate crowd, supportive message from the organizers, presentations every entrepreneur can related to, and serious fun.

Go find the perfect event for you. There will be people there you should know.

——

1For example, this academic study suggests so:  Morris, M., Webb, J., Fu, J., Singhal, S. (2013) A Competency-Based Perspective on Entrepreneurship Education: Conceptual and Empirical Insights. Journal of Small Business Management 51(3), pp. 352–369.

2 Pitchit is a new GTA thing where several startups are given ten-ish minutes to present their business to the crowd which contains a variety of potential investors and fellow entrepreneurs.

3There’s a mathematic model here somewhere, but let’s settle for: if there are three people, one of whom is determined to talk to everyone, and the other two who are cliquing, everyone will talk to everyone because the outgoing one will intervene with the other two. To get the idea of how many zealous networkers you should invite: multiple by one third of the number of expected attendees after subtracting the people who look like they are networking but are really running the event. Divide the program time by the time it takes for a good networker to have a conversation. Combine these factors. Do this in hexadecimal and it should predict the logarithm of the number of new dollars invested because of the event. 🙂

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What I Discovered at Discovery 2016 – Business with a Social Agenda

It’s that time of the year. Time to find out who has new ideas about turning which emerging technology into business at the annual OCE Discovery showcase.  With 3,000 other people, I spent a couple days networking, listening to keynote speakers from companies like Tesla, engaging with clever entrepreneurs, and hobnobbing with all the other folks who make innovation happen in Ontario.

I go to Discovery to learn: about what my colleagues are doing, new trends in business and technology, and new words1. There are always surprises.

Automobiles, obviously not new business but full of new technology, were big this year. In addition to a keynote speaker from Tesla, a panel with representatives from GM, Ford, Hyundai and IBM talked cars. First surprise – artificial intelligence is a driving force in the auto industry. I’ve been so focused on the philosophical aspects of how AI will impact humanity I forgot it would be soon be deployed in an everyday task. To drive cars.

A bigger surprise – the extent of the discussion on ethical issues related to electrical vehicles and autonomous driving vehicles. I can’t remember another instance at a business-focused conference where there was such thorough forethought (i.e. the opposite of afterthought) and time spent on considering the consequences to society and the environment related to a popular consumer product.

For the electric vehicles, the driving force behind the innovation is to cut carbon emissions and reduce global warming. But discussion didn’t stop there. Concern was expressed about the impact of the lithium in the batteries. This was countered by the responsible practices used in lithium mining, and the that the batteries are (almost) infinitely renewable, unlike fossil fuels that are burned and exhausted into the atmosphere. Of course, the source of energy for electric cars is electricity, the batteries are only the conduit, so the overall environmental foot print depends on the source of the electricity.

For autonomous or self-driving cars, there are many positives, including decreasing human suffering by eliminating human error as a cause of car accidents, and increased efficiency in route selection, leading to lower emissions (decreased driving times and less idling) and costs to maintain the roads. Cars that can drive themselves will be more convenient for human passengers, dropping them off at their destination and going to park themselves, saving fuel and decreasing human frustration.

Considerable concern lingers about the types of decisions the AI in an autonomous vehicle might make. In an emergency situation, it may be necessary to make a choice of who to protect from harm. If a collision between a pedestrian can only be averted by the car steering into a pole, which would be done? Does it matter how many people are in the car, how old each is, what their occupation, education or criminal record is? This is a truly scary thing to contemplate. But, encouragingly, auto- and AI-makers have thought about it.

Continuing on the theme of cars, Zipcar  is a company with a model for decreasing the impact to the environment of our transportation systems. Zipcar allows people to share cars owned by the company, in a very user friendly way. This should decrease the overall number of cars on the planet and therefore the energy and waste associated with manufacturing and recycling the vehicles. Robin Chase, cofounder of Zipcar, gave a keynote address where she elaborated on her idea2 that a solution to global warming lies in applying Zipcar principles to many other aspects of life: by using unused capacity we can decrease the world’s overall consumption of stuff. Her ideas are rooted in social change, but refreshingly embrace big business.

I found additional social innovation on the Discovery show floor, there were aisles dedicated to initiatives with accessibility-providing-technology, such as accessto.ca that lists restaurants, bars and cafes, describing how accessible their physical space is. There was also an area highlighting social enterprises.

Was the OCE Discovery program socially focused this year? I’m not sure I want to delve into motives. I’ll just enjoy the well-rounded perspective I discovered at Discovery on how tech business is developing.

1I learned the word fintech this year. This means new technological approaches to finance. Stuff like bitcoin.

2This is the subject of a book she is currently promoting, http://www.peersincorporated.com .

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