For over a year, I have using my device according to the guidance of Tristan Harris’s Take Control. It is like turning your phone into calming rather than anxiety machine. I recommend it for everyone.
After years looking into the science of consciousness, it seems to me that consciousness is “everywhere” – or at least in all sorts of unexpected places.
When my father developed dementia many years ago, I became curious about his consciousness as he slipped deeper into an Alzheimer fog. Several years ago I went to a conference, The Science of Consciousness, and since then have read several books related to the topic. The most recent one is “Superminds” by Tom Malone.
Malone summarizes the work in consciousness well by stacking it in a kind of hierarchy from the most basic idea of being conscious to the most esoteric, without venturing into the mystical (or dualistic) level. In other words, there are many ways to define consciousness and we can examine them using the tools of science.
The surprising outcome is we are surrounded by consciousness. It might be more abundant than life itself.
Here are the categories (he summarizes others’ work including “Consciousness” which I’m looking forward to reading):
Awareness. We could define consciousness as simply responding to the world. This is a distinction between being asleep and awake or whether one is under the effect of anesthesia. It also allows for something like a burglar alarm to be defined as conscious. After all, it takes inputs from the world and responds. Recently we’ve found that bacterial masses communicate information among themselves. And we also know that human organizations of all sorts are aware of their world under this definition.
Self-awareness. You might say that awareness is not enough. Well, perhaps the more is needed for consciousness. That an entity needs to be aware of itself and can tell others about itself. You can say you are hungry or confused. Humans can do this. But other animals can as well. Their communications may not be easily understood by us, for example, when a baby bird opens its mouth to signal hunger. And non-living things like my laptop or a car are able to communicate their internal states (charge me up!). Organizations, too, have processes to understand their internal states and communicate them. Consider, for example, financial reporting, as a way to communicate whether a company needs more funding.
Goal-directed behavior. The idea that a baby bird or your laptop is conscious might give you pause. Perhaps you want to define consciousness as taking intention action to achieve a goal. That is the intervention that seems to happen in our heads when we want to change what can seem like being on autopilot. When driving I sometimes find myself driving to the wrong place because, for example, I always drive to the kids’ school in the morning on weekdays. That daily drive could almost be done by a robot. But when I decide I have to drive elsewhere – downtown for a meeting – perhaps that is consciousness? But can we really say that many animals do not have intention when they pursue food, sex, and the other vitals of life? And there is the problem of understanding the intentions of another entity. Can we ever know whether there is intent in the mind of a salmon wanting to swim up river to its spawning spot? For that matter, what happens when TurboTax tries to figure out your taxes? That “intent” was programmed by developers, which in turn was developed collaboratively with the humans inside Intuit, the company that makes TurboTax.
Integrated Information. The evidence from neuroscience is that there are lots of types of information that are integrated during mental states that we associate with consciousness. This fact figures prominently in the Global Workspace Theory of consciousness. We know this happens in mammal brains, but what happens with a plant? Doesn’t it integrate information about sunlight, air, nutrients, and water to grow? I’ve even seen demonstrations of signals passing through plants in response to touch. And of course organizations like Wikipedia integrate information from lots of individual human and software editors to create an article. Perhaps Wikipedia is conscious?
Experience. The experience of being “like” something has been the definition of consciousness that is most widely used by philosophers, especially those who propose that consciousness is a “hard problem, ” most famously framed by philosopher Thomas Nagel asking, “What is it like to be a bat?” Malone walks through an example of how Apple (and most organizations) could be conscious in this way.
The most intriguing direction, though, has been work on Integrated Information Theory. It posits a mathematical description of consciousness that I am still getting my head around. The net output is a quantity, phi, that predicts the degree of consciousness of an animal, a brain, an organization, a circuit, or any information-processing network. It has interesting predictions, including some that are non-intuitive. For example, that if you replayed the neural code of an experience in a brain (assuming you could do that), it would not be consciousness. But that an LED with one bit of memory (a flip flop) has a minimal amount of consciousness. I found these two lectures helpful in understanding the concepts.
So it seems there are lots of systems that can experience consciousness. That experience, though, is not necessarily one we can relate to. What is like to be a flip flop circuit? I don’t know if any human can ever know that experience. Like so many times in our human history, like when we discovered that we are not the center of the universe over and over, the study of consciousness seems to show that human consciousness is not the center of the universe either.
I am on the last few chapters of a book by Tom Malone called “Superminds” about human organizations and the potential for software to enhance them.
I thought I would try an experiment and allow anyone to edit a document I’m creating to think about the ideas around the book.
You can find the document here. I hope you’ll read, comment, and edit it.
Some questions I’m asking myself about technology:
- Can we know whether a technology will have unintended consequences?
- How can we know whether a technology claim is bullshit? i.e. is there way to know whether a technology’s direction is likely to pan out?
- Is there a way to structure technology so it delivers on a particular social outcome?
- When should we adapt to our tech and when should it adapt to society’s demands? Can we ever count on technology to not exceed the bounds we (society) place on it?
- When will the rate of change of technology slow down or speed up? Can we better predict it?
- Was Marx right? Is capitalism + technology headed for a clash of classes?
The slow down of technology surprised me this week.
I’m writing this on an 11 inch MacBook Air made in late 2010. I dug it out of a pile of computers that sat unused for years. I wanted to blog and email while on this trip without taking my heavier, large-screen laptop and my experiment with an iPad failed because I like a real keyboard.
I thought about upgrading to the latest MacBook Air and realized that the fastest new ones are only about 3 times as fast, twice the RAM and about the same storage. While that is good, it is not the pace of change we are used to. This machine made nine years ago is still perfectly fine for writing a blog, browsing the web and handling email. Plus it is smaller than today’s machines (Apple discontinued the 11 inch model), making it perfect for travel.
Think of it. Laptops used to be obsolete after three years. This one is fine after nine!
What is happening? Technology is slowing down. The chips used in laptops and data centers are hitting limits imposed by physics. Clever engineers are still figuring out ways to pack more and more transistors into microprocessors, but they are resorting to weirder and weirder techniques.
In the era when Moore’s law had a clear path into the future, the strategy to increasing the size and speed of computer chips was reducing the size of transistors. Smaller dimensions allowed a smaller and smaller amount of electrons to do the work of computer logic – switching from one state to another at speeds of billions of times a second.
Now chip makers are stacking chips, rethinking the design of chips, computers, and transistors. These are all very clever ideas and some of them will work. But they represent many different strategies for overcoming the Moore’s law slow down.
Moore’s law of the past was not just a curve and a prediction. It was a common strategy embraced by many portions of the entire semiconductor industry. As a result, the benefits of increasing wafer size, decreasing feature size, increasing of clock speed, and a gazillion of other innovations were synergistic.
One little implication of the end of Moore’s law is that I am still typing away on this old laptop. A big implication I worry about is consolidation and ossification of the tech industry. I hope to dig into these ideas more and will keep using this old computer to do it when I’m on the road.
Last week my son and I did a road trip through the Olympic peninsula of Washington state. It was delightful. He created a road trip music playlist with old and new driving songs. It included songs I know like Sympathy for the Devil and songs by Metric. He also had a number of songs I did’t know.
At one point in the drive, he played a podcast of This American Life about Infowars and Alex Jones. I noticed that I got lost in the world of that story. I was drawn into the suspense. I shared the digust and the surprises as I learned of Alex Jones and his anti-christ bullying antics in high school. Every once in a while I would pull away mentally and notice I was no longer in touch with the scene around us. The cliffs, the mist, the lagoons, and the occasional raptor were lost from my awareness.
Listening to the music playlist was a different experience. It was a like a dose of a day dream drug. It tapped into the same feeling I have when purposefully let my thoughts drift. Somehow music enhanced the experience of watching the road go by. The Pacific coast and the trees all seem more interesting and alive.
All this led me to look into the Default Mode Network (DMN) and how it is influenced by music. The DMN is probably the most important “circuit” in the brain that you’ve never heard of. It are activated when you are engaged in self-reflection and empathy. It is also activated when you are day dreaming.
It turns out that, as I suspected, the DMN is deeply engaged when listening to music. Here is an interest snippet of what I learned from a survey article on the topic:
…it was not the genre of music or whether the music had lyrics, but, more important, whether the person liked it, that changed the patterns of brain functional connectivity. Analysis revealed that when a person listens to music he or she prefers, the brain increases connectivity within the Default Mode Network. This supports what people often report: They find themselves considering unsolicited personal thoughts while listening to music that they like. They are essentially ‘looking in’—ruminating on personally relevant memories and emotions—rather than ‘looking out’—paying attention to external events.“Because it is involved in rumination, where new ideas can be formed, it has been suggested that the DMN might influence aspects related to creativity, abstract thought processing, and cognitive flexibility.How and Why Does Music Move Us?: Answers from Psychology and Neuroscience
OK, so that seems to point to the DMN and daydreaming as connected and triggered by favorite music. What about narrative story-telling?
Well, that also seems to trigger the DMN, according to some studies. Here is a quote from that article:
The default mode network was originally thought to be a sort of autopilot for the brain when it was at rest and shown only to be active when someone is not engaged in externally directed thinking. Continued studies, including this one, suggest that the default mode network actually is working behind the scenes while the mind is ostensibly at rest to continually find meaning in narrative, serving an autobiographical memory retrieval function that influences our cognition related to the past, the future, ourselves and our relationship to others.
So where does that leave us? In the murkiness of science in the process of discovery.
The DMN is plainly a complex thing and we are beginning to decipher what it means for how we think, and how it influences the experience of being a human.
AI is increasingly looking like the demented HAL 9000 rather than the Star Trek computer. We can thank China for that.
China has seized on AI as a tool of control. The latest reporting by the New York Times indicates officials have deployed facial recognition specifically designed to profile, track, and control Muslim minorities.
This is different, but related to the threat that China might split the internet. That too is a battle with geopolitical implications, but this one is a greater threat to democracies including our own. China’s embrace of authoritarian technology means we might face those same technologies on our shores. Once a technology is created, it becomes easier to deploy it anywhere. While the first to copy China’s example will be other wealthy autocracies like Russia, Saudi Arabia, those products will become available to any buyer.
What happens when a Sheriff Arpaio type can buy these technologies?
The New Code War
In some ways, this is the inverse of the soft power the US and Europe have enjoyed by creating microcomputers, software, and the internet. Those technologies had ideologies baked into their creation by their libertarian skewing creators. Commenting on a recent Chinese technology trade show, a reporter noted, “If Silicon Valley is marked by a libertarian streak, China’s vision offers something of an antithesis, one where tech is meant to reinforce and be guided by the steady hand of the state.”
We have nothing less than a new war of ideology being fought over the future of technology. Instead of communism v. democracy, this new battle seems to be just a straight up authoritarianism v. liberalism. And the battlefield is code.
The Cold War was a geo-political contest of two countries with different ideologies under threat of a hot nuclear war. This war is about the future of code. We face the threat that our own system of capitalism will undermine our liberal democracies.
Perhaps this is the “new Code War” rather than the “Cold War.” I sense this battle will define our lives for the next many decades.
The New Code War frames a choice. We can seek to build AI and software that is like the computer from Star Trek, a smart assistant to humans that fulfills the vision of liberal democracies. Or we can allow the spread of a demented technology like HAL 9000 that is determined to follow the will of its master, no matter the dissent from mere humans.
When I evaluate a potential investment, which is more important?
The answer, of course, is “it depends.”
Generally, I lean towards team. A great team with a good idea can figure out how to get to a great idea or business. But a mediocre or bad team with a great idea will end up screwing it up. Of course, a great team with a bad idea is also not great.
This is not every investor’s philosophy. Especially as companies get larger and are measured on more traditional metrics of growth, revenue, margins, etc, most investors weigh the team as less important. And this is not irrational. By the time a company has gotten to a Series C or later they have probably figured out a viable venture model or not. At that point, the team is still critical, but it is far, far easier to hire new executives, including the CEO.
There are some VCs who just want to see the traction. Their attitude is, “massive traction is rare, but teams are replaceable.” These tend to be later stage investors.
For early stage investment, the team is crucial. Early ideas are literally embodiments of the teams that create them. I love ideas and I love getting to know people and their inspirations. So I guess it is natural that I tend to early stage investment.
My advice to entrepreneurs is surround yourself with the best people you can find that are also great collaborators. Collaboration EQ is generally more important than individual IQ. Research studies seem to show high functioning teams with diverse view points find better solutions than teams with a sole brilliant person or lots of conflict. Of course, sometimes you just want to build a team around a single genius person. But those are rare exceptions.
As an entrepreneur, you want to be in a category ripe for innovation with a team that can innovate, test, and recognize the signals of success.
Best Sources of Capital to Grow a Business
Only a tiny percentage of companies raise venture capital or should. Because it is one of the most exciting categories it gets more attention than other approaches. For most small businesses, other forms of capital make more sense.
I give this advice to entrepreneurs often:
Think of capital to grow your business as a hierarchy, starting with the cheapest to the most expensive.
The first source of capital to grow a business is money from your customers. Nobody will ever care about a product more than a customer or potential customer. Are you selling power bars? Make a few dozen and find some people to buy them. After that, find a few hundred, then a few thousand. Are you selling complicated technology that takes millions to build, like an electric car? If customers want it badly enough and the solution is good enough, perhaps a few will pay advances or put down deposits. Kickstarter and similar services have made this sort of capital easier to raise than ever. For more mature companies there are ways to get capital up front for purchase orders and receivables.
Second, consider government. There are often many sources of capital or loan guarantees to help small business. The Small Business Administration is a potential resource. For technology companies doing deep technology, government agencies like NSF, DARPA, NIST, DOD, and government labs are often great ways to prove out a basic technology. Yes, it can take a long time to get through the process, but it is a really cheap source of capital.
Third, think about debt. Obviously an early stage company will not get a loan from a traditional bank without a personal guarantee from the entrepreneur. I do NOT advise entrepeneurs to go into personal debt to start companies. While debt can be really hard to secure, think about customers, suppliers, and others who have a stake in your success. They might be willing to take the risk when traditional sources would never do it.
Finally, consider venture capital if, and only if, you have a company that meets all these criteria:
- Addressing a big problem that translates to a large market opportunity (at least a billion dollars a year in revenue within 10-20 years)
- Has the opportunity to build a strong differentiation from competitors immediately
- The differentiation can grow over time, creating barriers to entry
- You and your co-founders are willing to accept dilution and are willing to give up some control of your company. Also, you need to be prepared to potentially give up full control over decisions like sale of the company, future money raising, and who is the CEO.
This is the sort of company that can make money for venture investors. We are looking for a future when the company is growing rapidly (revenue growth of 50-300% a year) and has large margins (more than 30%, ideally more than 50%). And future investors or acquirers of the company expect that growth to continue.
If, instead, you forsee a company with very predictable profits and steady but slower growth, there are other sources of non-venture equity that might be better. These are the conditions that companies like restaurants and commercial real estate experience. They have different funding structures and different types of investors.
Each of these steps can build credibility for the next. A company that has already sold some product at a profit, has a loan from a supplier or customer, and has won a competitive government grant or contract is way more attractive than a raw startup of some people and an idea. This is especially important for ideas that are either the bleeding edge or categories that might be out of favor. Why? Because all those points are validation that you are solving something important.
If you are having trouble raising venture capital, try re-thinking how you could raise from a category higher in the hierarchy. That might all you need. Or it might set you up for venture capital in the future.