Empowering innovation

The massive opportunity is to drive innovation and faster iteration, by empowering domain experts who know what an application should do, even if they don’t have the coding skills to execute themselves. The communication gap between what a user needs and the developer is a massive inefficiency.

Risks of citizen development

As developers often point out in response, users don’t actually know what they want, and the value they provide is to help frame what is required and the path to get there.

Moreover there are hidden costs to enabling citizen development. The most obvious is that individual don’t see the big picture, so may be duplicating what has already been done, may not create quality apps, interface design will likely not be consistent with the other applications, making it harder for other users.

The fragmentation challenge

A particularly important point is that development pushing out to end-users almost inevitably creates fragmented systems, with a proliferation of apps hard to integrate with existing platforms.  

This makes it harder to create unified digital experiences, and risks to data integrity unless clear measures are in place on data access and storage.

Technology governance for transformation

As we have already learned over many years already, the more technology development is put in the hands of end-users, the more we governance structures and oversight are needed. This is very obviously required for security as well as maintaining the integrity of enterprise systems.

The challenge is to establish this in a way that enables the power of citizen development while keeping effective enterprise system structures. As I often term it, “governance for transformation“.  

It is hard to get right, but the rewards of doing this well are massive, creating an incredibly agile, innovation organization that is stable as it rapidly evolves. 

An interview in Financial Times shares his perspectives on the role of AI in work. As Autor emphasizes and I have been saying for many years, the issue is in the design of work and the economy, and the mental models we apply to how we do that.

The whole interview is worth reading, here are a few excerpts.

“I think AI is going to reduce the bottleneck of expertise in some areas, but that can complement others. There are many paths where you have foundational judgment, acquired through experience or training, bounded by some upper bound of technical or specific knowledge… The good case for AI is where it enables people with foundational expertise or judgment to do more expert work with less expertise. 

…

We do see reduced hiring at firms adopting AI in some of the tasks that AI is good for — information processing, some software coding, decision-making tasks. But I don’t think that is in any sense a full description of what’s going to occur. It’s actually a challenge of job design to figure out how we reallocate and redesign work, given the tools we now have available. This often takes a long time to figure out.

…

The question we should be concerned about is not the number of jobs. We have a labour shortage throughout the industrialised world. I am concerned about the number of jobs in Mumbai, but in the UK, in the US and northern, western Europe, we are running out of workers. The concern we should have is about expertise. If people are doing expert work that pays well and now they have to do generic work that pays poorly, that’s a concern. It’s the quality of jobs, not the quantity. The problem is technology can make some expertise much, much more valuable, but in other cases, it directly replaces expertise we already have.

…

Technology can be both very helpful or very harmful. It’s helpful to the degree it complements expertise and makes people’s skill set more valuable by allowing them to do more with it. It’s harmful to the degree that it takes skills that we’ve invested in that are the basis of our livelihood and makes them so abundant that they aren’t worth anything any more. I think we have a real design choice about how we deploy AI. It is so flexible, broadly applicable and malleable that we can do lots of stuff with it, some quite good, some quite bad, and depending on the mental model we have in mind of what we’re trying to do, we will accomplish different things.

…

If we could reinstate the value of mass expertise by enabling people to do more in the trades, in healthcare, in contracting construction, in even some of the writing tasks that we do, that would be spectacular. If it comes at the expense of making some elite expertise less scarce I think that’s ok. I don’t think people with PhDs and MDs and JDs are going to be wiped out. They may just not see the same year over year wage growth that they’ve seen over the last several decades. That’s ok. They’ve had a good run and they’ll be fine.”

Hopin was valued at $7.6 billion and now appears to be valued at around $400 million.

Verizon paid $500 million which is now effectively written off.

Run the World raised $15 million including from Andreessen Horowitz. While a sale price wasn’t disclosed Techcrunch noted that there were 500 events recently listed, down from 15,000.

What went wrong?

Not dissimilarly to the dramatic back-to-office shift after Covid remote work, now that we are able to do events in person, demand for virtual events has plummeted.

Akin to “travel revenge”, everyone is keen to get back to in-person events. My professional speaking was for two years entirely virtual. This year I have been back to travelling around the world, with only one remote presentation all year.

But another important point is that none of these platforms ever created a compelling virtual event experience. They were all largely based on physical event metaphors, and while there a handful of interesting innovations, none brought them far beyond a glorified video call.

Will we get to a point where we can have engaging virtual events in the Metaverse, using avatars and next-generation glasses?

Probably, but the timeline on this, including people becoming comfortable with the new environments, is likely 5-10 years.

In the meantime virtual events will still be significant and a gradually growing proportion of overall events. But virtual event platforms are unlikely to be a massively lucrative sector. 

After a break during Covid, I’ve been back briefly 4 times in the last 8 months, usually en-route to US speaking gigs, catching up with people, going to events, and getting a bit of a feel for the city post-pandemic.  

In my conversations here I’ve experienecd deep division of opinions on the state and future of San Francisco, with some seeing it as well past its peak following an exodus over the last years (“it’s a shithole”), while others believe it is in the early stages of a renaissance (“everyone’s coming back”).

As a visitor I don’t personally experience the issues facing the city to any significant degree, but it is interesting to reflect on some of the factors and how those may play out.

Knowledge networks, especially in AI. The Bay Area has long been the global leader in tech startups, substantially due to the intensity of world-leading expertise in the region. Those on the edge learn from each other, and want to be here to keep ahead. With AI transforming the world and AI capabilities centered on San Francisco, people are coming back to town.

Reversion of remote work. Many people left the city when remote work was possible and encouraged. Now many tech and other companies are enforcing back-to-office, resulting in people moving back to the city. However this ismight be a short-term trend. The degree to which tech companies hire remote or local workers will fundamentally shape the city.

San Francisco vs Silicon Valley. During the 2010s I observed a substantial shift in the center of gravity of tech from mid to lower Silicon Valley to San Francisco. All the major tech companies located in the Valley set up SF offices, some relocated, and many new companies set up in the city. Not least in the reasons was that young dynanic people wanted to live in a vibrant city, not in the ‘burbs. The center of gravity could shift back, but the city is still vibrant, with most major AI companies in San Francisco. Venture capital is equally available across the Bay Area, though some investors prefer or mandate that companies are in the region. 

Inequality, crime, drugs, and homelessness. The city’s social problems are legion, impacting the poor and making some parts of the city dangerous and unpleasant. Extreme wealth disparities inevitably create deep challenges, and there is little prospect of these easing. San Francisco apparently has the lowest proportion of young children of any city in the US, with parents choosing to live elsewwhere.

Real estate prices and cost of living. Many have already left the city due to the high cost of housing, though this applies across most of the Bay Area. As seen in other cities, the cost of living could drive out more of the creative community that helped to make San Francisco the colorful, dynamic city that it has been for many decades.

Politics. In short, there is much current or future city governments could do to improve the city, but it is highly uncertain whether they will be effective.

Transport. Improved transport could enable people to live outside the city but work in San Francisco, balancing quality of life and work demands.  The prospects for dramatically better public transport in the foreseeable future are low. However autonomous car or buses could allow low-cost transport for many.

Regulation and tax. A number of companies have relocated out of San Francisco and California due to higher taxes and a greater regulatory burden. The advantages of being located in the city, such as access to talent and tech ecosystems, need to outweigh these costs.

Community and values. There are extremely strong communities in San Francisco, many building strong bonds through doing ventures together. Many people have aligned values around positive social impact and expanding consciousness, with these communities sometimes harder to find in other US cities. 

Personally I have found it exceptionally intellectually stimulating being here in recent visits and I intend to get back more. It still feels like a second home to me, so I hope that it prospers.

It’s a great exercise. When I first read the article and listened to the accompanying podcast, I found myself agreeing with just about everything, but it still left me deeply unconvinced on some aspects of the piece. So it’s been good to go back to it in depth. 

We were given a spreadsheet containing all 320 sentences in the article, as well as a list of 128 summarized general claims, and invited to providing supporting, refuting, or refining arguments. Here is the argument spreadsheet if you would like to add any arguments yourself! 

Here is part of what I contributed to the debate mapping, commenting on Andreessen’s statements.

“AI will not destroy the world, and in fact may save it.”

The first part of this sentence is a statement of belief. In fact very little the article directly supports this statement. 

The second part of the statement is not directly supported in the article. however it extensively describes many of the ways that AI could have substantial positive social benefit. Which is not the same thing as saving it.

The fact that there can be substantial positive impact in a variety of domains does not, in fact, repudiate the potential for AI destroying the world.

Much of the article argues that there is a moral panic about AI, with many of the major protagonists benefiting from this panic. Andreessen himself writes that:

“it’s not that the mere existence of a moral panic means there is nothing to be concerned about.”

He then goes on to focus on the fact that we have an AI moral panic, which is probably a fair assessment but does not validate his broader case.

One of the most pointed statements Andressen makes is:

“The claim that the owners of AI will steal societal wealth from workers is a fallacy.”

There are a few problems with this. It is an assertion with little subsequent substantiation.

“Steal” is an emotive word and an active verb. Even if there were no intent to take wealth from workers (a generous assumption), that could happen naturally due to an array of factors. In fact recent U.S. labor share of GDP has decreased substantially from any time prior to 2008.  

Given the extraordinary economic and social value that Andreessen professes AI will give us, it would be extraordinary if the companies that own the most used AI will not accrue a very high proportion of economic value. 

I personally agree with Andreessen that we are likely to have strong employment into the indefinite future. However the disruption to livelihoods and lives as existing roles are eliminated or reshaped by AI could still be brutal, and there is no evidence that the well-documented polarization of work will not continue. 

Andreessen also argues that AI will not kill us all. 

“AI is not a living being that has been primed by billions of years of evolution to participate in the battle for the survival of the fittest, as animals are, and as we are. It is math – code – computers, built by people, owned by people, used by people, controlled by people. The idea that it will at some point develop a mind of its own and decide that it has motivations that lead it to try to kill us is a superstitious handwave. In short, AI doesn’t want, it doesn’t have goals, it doesn’t want to kill you, because it’s not alive. And AI is a machine – is not going to come alive any more than your toaster will.”

The specific words here are important. Andressen’s argument why AI will not kill us is founded on two concepts:

“AI doesn’t want.” However just because AI doesn’t have explicit volition doesn’t mean it won’t engage in non-huiman-aligned action.

“AI is not going to come alive.” This is in fact highly debatable, and has no direct bearing on whether AI may kill us all. 

As such these are by no means solid arguments.

These points I’ve addressed above are where Andreessen’s article is weakest. I do agree with almost all points that he makes. But the things he has justified the most thoroughly in the piece are not in fact his central points, which he essential presents as assertions.

I and others consider these assertions to be (highly) questionable. 

Yet a belief in the concept of accelerating returns in all its guises has been central to my life, and you certainly can’t discard the idea of the Singularity. The inevitability of it happening as described is more debatable.

However ssince November 30, 2022, when ChatGPT was launched, many of the ideas of the Singularity are not only far more current, they have become central to discussions across many dimensions of society. 

With the advent of generative AI with all its manifold implications, it is worth coming squarely back to the idea of the Singularity.

The problem has been that whenever two people talk about the Singularity they think about it in different ways. It is not one thing.

To help disambiguate, I’ve created the Six Facets of the Singularity framework, shown below.

Some of the facets complement or fit with others, some contradict each other. The Singularity is not an integral concept. It is open to our interpretation, and indeed if we transition into and through it we will each understand the process in a different way.

These facets can be debated and discussed, but the intention of the framework is to give us a common frame to discuss the Singularity.

How does each of us relate to these different facets? Collectively that could determine our future. 

Accelerating Returns

Each technological advancement fuels further innovation, creating a cycle of exponential growth that speeds up the rate of progress.

AGI > Humans

Artificial General Intelligence could surpass human intellect in every domain, transforming society and the economy.

Transhumanism

Integrating advanced technologies with human biology could redefine humanity, radically augmenting abilities, extending lifespans, and migrating minds.

Superabundance

Technologies including AI, nanotechnology, and additive manufacturing could render traditional economic constraints obsolete, enabling a post-scarcity society.

Existential risk

Acceleration entails significant risks, potentially leading to human extinction or other catastrophic outcomes if we cannot control unprecedented technologies.

Event horizon

We may reach a point beyond which uncertainty and the pace of change exceeds our capacity to foresee or understand future developments.

Image: Midjourney