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Singularity Summit - Margit Mansfield

September | Development and Growth | Read time: 1 minute

Singularity Summit: Create the Future

The Singularity Summit, presented by SingularityU, brings together 2,000 changemakers for talks on AI, AR/VR, blockchain, the future of work, impact, investing, robotics, and more. Consultant Margit Mansfield discusses her key takeaways from the conference.

Key Insights

  • The importance of inclusion across industries regarding AI advances
  • How businesses and people can better prepare for the future of work
  • The importance of disruption and purpose-led change

As an attendee of the recent Singularity Summit in San Francisco, a key interest of mine was in exploring how exponential technologies are shaping the world and, more specifically, the future of work.

Facilitated by SingularityU, their premier annual gathering brings together 2,000 changemakers for talks on AI, AR/VR, blockchain, the future of work, impact, investing, robotics, and more. 

So, what will the future work ecosystem look like? How can we improve our current models to match what we will call work in the future? 

Why the Singularity matters for all businesses (and people)

The “Singularity” is the point at which computers become as smart as humans. Many futurists and scientists predict that, once reached, computers could improve themselves, quickly outpacing humans and thereby becoming their evolutionary successors. 

Already, IBM’s Watson has defeated humans at chess and Jeopardy. Amazon’s Alexa can predict when you’ll need to order nappies. But as for the Singularity, we’re still at a stage of predicting when it will happen, and what will happen afterwards.

That’s when, not if.

It’s predicted that 40% of the world’s current positions will be automated within 15 years, and we can’t afford to put off how to deal with these challenges until tomorrow. 

Many of the esteemed speakers at the event propounded that industries and governments need to start changing the way we define work, and better prepare leaders and organisations to deal with AI integration.  

One way to understand how we might do this is to look at how organisations take advantage of AI right now.

“Disruption isn’t hard because of technology, it’s hard because of people.” – David Roberts 

Speaker Nathana Sharma highlighted that early adopters of AI will secure exponentially larger gains for the future. For example, insurance firms are gaining a competitive edge through implementing machine learning to assess whether an insurance claim is fraudulent or not. 

The future work landscape will look fundamentally different, which emphasises the importance and urgency of this conversation. Organisations need to consider their ‘why’ and the social impact they want to have.

So what might you need to consider as the AI revolution marches on?

1. To change what you do, you first must change how you think.

MJ Petroni from Causeit called for the “need to unlearn.” Delving further, that means needing to shift from incremental thinking to exponential thinking. We must constantly update our maps.

By blending a bit of old and new, we can help people make the transition to a new way of thinking. For example, the public wasn’t ready to shift from horse & carriage transport to the automobile. Automakers created the somewhat skeuomorph horseless carriages first – allowing people to become used to the idea – that way, it wasn’t that big a leap to the automobile.

To help people along the ‘exponential journey’, a strategic narrative is key. Part of that narrative is a powerful shared purpose, one that goes beyond the individual and organisation. And that purpose must be a catalyst for action with customers and make a positive impact on the world. 

A purpose-driven organisation is more likely to succeed at exponential growth.

The rise of the social enterprise was a common theme at the Summit. This conversation has already started but it’s one that is gaining momentum.

Maximising shareholder value can no longer the most important thing at the expense of all else – to survive, organisations must consider multiple stakeholders.  

2. Leverage team and peer learning

Exponential learning is key to exponential growth. John Hagels’ work at Deloitte suggests that groups of 5 to 15 people joining together with a deep commitment to learning delivers the greatest results for exponential learning. 

This is relevant to learning platforms when it comes to scaling, to create workgroups which are connected to one another and learning from another.

An out of the box example here is big wave surfers. These daredevils come together on local surf breaks to learn, but are also connected through a global learning ecosystem.

Current technology platforms can and do enable this model to function, but many organisations aren’t seeing the results expected as they continue to handle connection in a manual way.   

3. Disrupt yourself

That’s both on an individual and organisational level.

If an organisation isn’t already thinking about disrupting their own business models, they are likely to be left behind. 

If individuals aren’t considering how they might upgrade themselves constantly, they too, will very quickly become outdated.     

Organisations don’t have to invest heavily to start deploying AI. There are many cloud-based options available.  For example, if you can’t afford a data scientist or analyst, then marketplaces like Experfy are available to you.

Which brings us to Amin Toufani’s talk on digital twins and exponential business models, which was especially enlightening. 

By being able to create a virtual twin of say a process, a set of behaviours, physical activities, or product parts (e.g. a jet engine), organisations can disrupt and grow. 

Using telematics in cars has enabled the insurance industry to understand driver behaviours and dynamically price their products based on this behaviour.

Toufani foresees that over time, most industries will be disrupted and are likely to become technology companies that provide a product or service rather than a retailer or insurer for example.

He warned that, “the vast majority of companies think they are at the centre of the universe”, though with the advances in AI and machine learning, that attitude is held at their peril.  

Individuals need to be proactive, however organisations have a responsibility here (Amazon is already upskilling their teams to work with AI). Another speaker, Adam Medros argues that companies should see this development as a CSR initiative.      

How willing are organisations and their top leaders to go here? How much leadership development is focused on unpacking your deep beliefs and helping you shift them if need be? 

What is your disruption quotient? – Charlene Li

4. Focus on future customers

New York Times bestselling author, Charlene Li, talked about a disruption strategy for organisations which starts with a focus on the future customer. Importantly, creating a leadership movement that’s aligned with the future customer. 

Becoming customer-focused (the real deal, not a cliche buzzword) may involve short-term sacrifice. When Adobe moved from a packaged software model to the cloud, they knew revenues and income would plunge. However, their share prices did not, now they have increased the value of their stock price almost 10x in 7 years. 

There is certainly a rise in customer-centricity, but how much of that is focused on future customers. And how willing are organisations to make present-day trade-offs in order to meet the needs of the future customer?

5. Embrace experimentation and failing

Chair of the AI and Robotics Track at Singularity University Neil Jacobstein posited that the only way to make real progress is through experimentation; which means failure and lots of it. 

The ability to embrace failure is part of the DNA of among start-ups, particularly those that are tech-based. How can more traditional organisations learn from this? Many companies talk of embracing failure, but the prevailing systems and leadership approaches don’t facilitate or encourage this. 

Perhaps the only place we need to be failure-averse is in our ethics.

For example, while autonomous vehicles currently are not perfect, they are still better than humans (considering how many people are dying on the roads because of human error). 

Jacobstein mentioned that real progress was being made on AI safety and security and empathises that AI must be designed for security, ethics and future guidelines.

He argues that the ratio of new vs displaced jobs is key, that the timing is uncertain, and that a basic income and free education should be considerations in the future. 

Exponential growth cannot happen without embracing experimentation. It also can’t happen without governance.

6. Embrace new and non-traditional ways to think about the future

Managing Director of Innovation & Design at SU, Christine Kelly, talked about exponential technologies obliterating our assumptions e.g. meat from animals, human drivers. 

Kodak understood photos as objects. What photos are now is a way to chat, communicate brands, prove social currency, etc.  

It stands to reason that we should use tools that help us suspend judgement, disbelief, and fundamentally shift our perspective to think about the future.   

The power of story, strategic narrative, and even using graphic novels as a tool to create a shared vision and story is one such method. Given exponential growth, we cannot rely on the past or present to predict the future.

Keogh has been encouraging these concepts for some time. Executives should be prepared to entertain something that is outside their comfort zone if they are to shift their perspective.

Sometimes the wild, crazy ideas and unconventional approaches to get there are just what an organisation needs to shift.

7. Diversity and inclusion start at home

The importance of diversity and inclusion came to the fore several times throughout the Summit.

It’s a big deal and certainly a focus of the organisations we work with. I did love Dr Makaziwe Mandela’s take on this (daughter of Nelson Mandela). Her message: diversity and inclusion is about kindness, compassion, sharing and love.

She argues that this starts at home, in your own backyard. You don’t wear the racism jacket at home and take it off at work. So, while organisations talk about unconscious bias, targets, appointing more women to Senior Executive roles (all critically important and worthy things we must do), perhaps we also need to be talking about kindness, courage, love and compassion. To Dr Mandela, that means including families in this conversation.  

How many inclusion workshops have you brought your family to? 

Conclusion

While there was certainly a sense of optimism about what the future could look like, there are a lot of unanswered questions surrounding ethics, privacy and governance. 

Who is creating the algorithms and what problems are we asking machines to solve? History shows that not all new discoveries or technologies are used for the benefit of all humans.  

While AI may help us solve global warming, it also has military applications. There is much progress in the area of ethics and governance but every organisation adopting AI needs to be part of this conversation. 

Inventor and founder of Komposite, Pablos Holman, put it: Let’s be clear about what we want to use Artificial Intelligence for.  

He makes a strong point that algorithms need to learn what we care about. They can help us solve global warming, or a better app for selfies. For example, machine learning in India has been used to predict malaria outbreaks, and where drought is likely to occur.

“Vision without action is a daydream. Action without vision is a nightmare.” – Japanese Proverb

Ray Kurzweil (futurist and founder of SingularityU) predicted that by 2030 we will be able to connect our neocortex to the cloud. He too paints an optimistic view of the future, where machines will enable us to have “superpowers.”

But while the digital experience has always been a human experience, if we are to eventually become united with machines, what will it mean to be human?  

As for me, my next step is to enrol in an online course on machine learning. And so my own disruption journey begins.