The Shape of Things to Come
Issue 79: Oct 27, 2022
As we contemplate the end of another year, now is a good time to revisit the opportunities and shortfalls of technology. And to clear up some popular theories that may be losing ground. As we have said many times, technology is no panacea or silver bullet, it is simply a tool to augment our intelligence, make our solutions smarter and help us measure what matters in a way that matters. Remember, machines and applications have no goals and no agendas. They have no values or ethics. They are task-based operating on the programming we input and the function we have established. The bigger they get, the more hidden are their failures. There is a fundamental distinction between thinking and knowing. And most critically, they are programmed and coded by human beings with all their strengths and inherent biases and therefore, are and can be as faulty and error prone as we are.
That said, there are some new technology threads in the popular conversation that have caught the imagination and attention of forward-thinking leaders and their organizations. We’ve curated three big ideas that we think are worth paying attention to with a few predictions of our own of what these technologies can do for us.
This open-source nonprofit collective has been working on developing natural language systems that have relevance to our organizations and our social institutions. OpenAI is self-described as having a mission to ensure that “artificial general intelligence (AGI) are highly autonomous systems that outperform humans at most economically valuable work that benefits all of humanity.” Okay, that’s ambitious and optimistic. It adds, supporting the altruistic open-source credo, “We will attempt to directly build safe and beneficial AGI, but will also consider our mission fulfilled if our work aids others to achieve this outcome.”
Here’s the kicker: “Our first-of-its-kind API can be applied to any language task and serves millions of production requests each day.” How do they do this? We are sharing two of their technologies that we believe are going to change our lives, professionally and personally.
GPT-3 (Generative Pre-trained Transformer 3) is technically an “autoregressive language model that uses deep learning to produce human-like text. Given an initial prompt, it will continue to produce text that matches the prompt.”(Wiki) Another description: It performs a wide variety of natural language tasks, which translate natural language to code. That’s a mouthful for non-tech heads, but its implication for organizations is profound.
A simple description of the way it works from TechTarget is “a neural network machine learning model trained using data to generate any type of text. It requires a small amount of input text to generate large volumes of relevant and sophisticated machine-generated text. GPT-3’s deep learning neural network is a model with over 175 billion machine learning parameters. To put things into scale, the largest trained language model before GPT-3 was Microsoft’s Turing NLG model, which had 10 billion parameters. GPT-3 is better than any prior model for producing text that is convincing enough to seem like a human could have written it.”
And that is the lynchpin to our fascination with GPT-3. We will be able to generate marketing messaging, content, advertising, blogs, chatbots, customer service systems, voice commerce, voice assistants (Siri and Alexa) – just to name a few – that will evoke the same syntax, cadence, language, and empathy as a human being. TechTarget adds, “GPT-3 has been used to create articles, poetry, stories, news reports and dialogue using just a small amount of input text that can be used to produce large amounts of quality copy. It is also being used for automated conversational tasks, responding to any text that a person types into the computer with a new piece of text appropriate to the context. GPT-3 can create anything with a text structure, and not just human language text. It can also automatically generate text summarizations and even programming code.”
That is either something to celebrate or be terrified by. When do we know we are talking to a human? Reading an article written by a human? How can we have confidence in the answers to our questions? Can GPT-3 really understand and respond to the nuances of our words and respond appropriately?
It surely is a powerful tool that every organization may be using in the future to leverage its augmented intelligence to produce services, systems, and products. The need for urgency will become strong and loud from the innovators, both on staff and as consultants. They will advocate this technology as a solution to many problems, to create new efficiencies, a tool to speed customer response, and fill task gaps in a shrinking workforce. Anticipating this augmented intelligence system, what new knowledge and skills will an organization need to ensure its effectiveness in terms of its business model? Will the promise become reality?
Future iterations will only get better and more powerful, and we will surely become highly immersed and deeply dependent on these technologies. But, let’s offer a reality check. GPT-3 is programmed by human beings, and we know that information generated by humans is often a victim of conscious and unconscious bias. GPT-3 “suffers from a wide range of machine learning bias. Since the model was trained on internet text, it exhibits many of the biases that humans exhibit in their online text. For example, two researchers at the Middlebury Institute of International Studies found that GPT-3 is particularly adept at generating radical text such as discourses that imitate conspiracy theorists and white supremacists. This presents an opportunity for radical groups to automate their hate speech. In addition, the quality of the generated text is high enough that people have started to get a bit worried about its use, concerned that GPT-3 will be used to create fake news articles,” reports TechTarget.
In our book, The Truth About Transformation, we stress the importance of healthy skepticism and critical thinking to unpack bias in all aspects of organizational systems, strategies, products, and services. Taking a momentary pause to consider and evaluate what we are experiencing, reading, viewing, or consuming isn’t typical. By nature, we are trusting, wanting to believe what is put in front of us and do not expend the energy to question. GPT-3 with all its ability to create wonder and awe also has the ability to perpetuate the practice of misinformation, communicate half-truths or present solutions, calculations or findings that may not account for all necessary factors and variables if it is not managed. We as humans have the responsibility to ensure that GPT-3 and its next generation iterations are used, as OpenAI intends, to benefit humanity, be leveraged as a tool by humanity and not undermine its foundations and beliefs. That promise in reality is surely going to be much more challenging than it sounds.
We’re sticking with OpenAI for another of its brilliant breakthroughs. The purpose of art is a philosophical question that we are not equipped to answer here. Yet some observers claim that artificially created imagery is better than the real thing – and more pleasing. DALL-E (a mash-up for Salvador Dali and WALL-E) is a machine learning model developed by OpenAI to generate digital images from natural language descriptions using a version of GPT-3 to generate images. (Wiki). Look at the image we choose created by DALL-E for this report; a prompt to draw an astronaut riding a horse in space.
OpenAI explains that DALL·E can generate a digital image from scratch. Just to put it into perspective, the system controls multiple objects, their attributes, and their spatial relationships. OpenAI adds, “consider the phrase a hedgehog wearing a red hat, yellow gloves, blue shirt, and green pants. To correctly interpret this sentence, DALL·E must not only correctly compose each piece of apparel with the animal, but also form the associations (hat, red), (gloves, yellow), (shirt, blue), and (pants, green) without mixing them up.”
So, college students use GPT-3 to write their papers (their professors are now onto this practice and grade them accordingly) and to play with DALL-E to try to trick it. But practically speaking, GPT-3 has many relevant applications in business, as does DALL-E. For example, you are creating a presentation and need to illustrate it with an image that represents exactly what you are proposing. Instead of struggling to find scrap art or stock photos, DALL-E with the appropriate prompts can produce exactly the image you need. Or think about product catalogs, fashion, interior design, website imagery – even refreshing an organizational logo. All of this can all be generated digitally. And with DALL-E, you own the imagery and do not have to pay a third party for the rights. As a cautionary note, graphic designers might want to master the technology now to use it to augment their talents and not be disintermediated by it.
Love it or hate it, the metaverse is not going away. It is becoming part of the public discourse as we often relish what is possible. We delight in the potential societal impacts of technology and seek to turn the “make-believe” of science fiction into our day-to-day reality. Whether it be the now-nostalgic narratives of Star Trek, the Jetsons or Jurassic Park, many of us accept the stories as potential visions of future … and some work to turn those visions into reality. The hype of the metaverse needs to be balanced by critically thinking minds. Yes, some promised applications in virtual worlds may help solve problems we have in real life and enable connections not physically possible, but we should question if the metaverse will become all things to all people.
If we reflect on the Pixar movie WALL-E, it told the tale of the advances of technology and exponential growth of the human race that left the planet a trash heap. Humans escaped Earth and lived in a majorly sedentary unhealthy life on spaceships, constantly immersed in a virtual world. Pixar represented the future human race as obese, lazy, and highly dependent on technologies. Is this the future we really seek? Will the creative and scary vision of the movie’s creators come to pass? And is the metaverse the crux that begins it all? Whatever side you are on, science fiction in literature and films are usually a few steps ahead of the rest of us and perhaps subconsciously preparing us for the shape of things to come.
The Metaverse at Work
Accenture claims “The Metaverse Continuum will transform how organizations interact with customers, how work is done, what products and services they offer, how they make and distribute them, and how they operate their organizations.” Integral to building multiverse activations, “Organizations will find themselves on the front lines of establishing safety and defining the human experience in these worlds. Trust will be paramount; existing concerns around privacy, bias, fairness, and human impact are sharpening as the line between people’s physical and digital lives blurs. Leading enterprises will shoulder the charge for building a responsible metaverse and are setting the standards now.”
The consulting firm has four predictions for how the metaverse will be assimilated into our lives:
- The internet is being reimagined. People are now living virtual business lives to an extent they never expected. The metaverse is emerging, reconciling how the internet is designed. Practical application from Accenture: “BMW is building digital twins of 31 different factories. The models use real-time data to recreate a 3D environment that is a living mirror for everything from the machines on the floor to the people working at stations. The environment is used for a wide range of functions including training robots to navigate the factory, bringing together designers from across the globe to experiment with new line layouts and training simulations for individual tasks.”
- The value of new virtual worlds would be limited if there are not parallel changes that anchor them in the physical one. Accenture states the convergence of new technologies like 5G are changing the way organizations interact with the physical world and unlocking an unprecedented level of control, automation, and personalization. The digital models of the physical world give organizations real-time insight into their environments and operations. According to Accenture, the global digital twin market, valued at $3.21 billion in 2020, is expected to reach $184.5 billion by 2030. On-demand and hyper-customized products are a material reality. For instance, 3D printers can now print a much wider variety of objects with new kinds of smart materials and programmable matter, which can change physical properties on demand, will make it possible to customize products after production.
- What is real and what is a “realistic” unreal version of reality? We will live with machines that could pass as human. Unreal qualities will be used for good and bad, including deepfakes and misleading bots. Accenture warns that synthetic data and images, chatbots and AR are forcing the issue of what’s real. Is the DALL-E image real? Is the customer service rep human? Does it matter? The existential argument will be dominated by whether systems run more smoothly, customers are more satisfied and whether the unreal will provide more stability, predictability, and security.
- The outer limit of what is computationally possible is being disrupted as a new class of machines emerges. According to Accenture, quantum, biologically inspired and high-performance computers will allow companies to tackle the biggest challenges in their industries. High performance computers (HPC), or massive parallel processing supercomputers, can help businesses make use of huge swaths of data that are too expensive or inefficient for traditional computing. As Accenture describes it, biology-inspired compute draws inspiration from, or relies on, natural biological processes to store data, solve problems or model complex systems in fundamentally different ways.
As we included in our book, Dr. Greg Stock, author of the Book of Questions and CEO of Socratic Sciences, states that “the metaverse is definitely going to happen for specific niche audiences including leisure, recreation and gaming.” He sees a full-scale parallax view as seductive but an unattainable fantasy. Its development will be controlled by ongoing tech innovations and iterations, necessary to make it practical to a wide audience: better visual interfaces and high-speed connectivity. His view of the future is more O2O – online to offline engagement. O2O, is used in digital marketing to entice consumers within a digital environment to make purchases of goods or services from physical businesses. He believes that O2O technology can facilitate remarkable conversations and community building to give workers a voice and develop meaningful, lasting relationships with co-workers blending online with offline interactions.
We selected these technologies for a reason While it may seem like science fiction if you are working daily to increase memberships, subscriptions, and sales, each of these emerging tech solutions has a play in how you can improve your systems to improve your products and services.
There are a few other frontier and emerging technologies that reflect the work of OpenAI that may be the most disruptive. Here is a curated list of megatrends via Gartner that will impact our day-to-day lives.
- The Smart World: Within three to six years, a smart space will be a “physical or digital environment in which humans and technology-enabled systems interact in increasingly open, connected, coordinated and intelligent ecosystems. Smart spaces can be referred to as smart cities, digital workspaces, smart venues, and ambient intelligence.”
- Productivity Revolution. Within six to eight years, “generative AI learns from representations of artifacts from the data and uses it to generate brand-new, completely original artifacts that preserve a likeness to original data. The field of generative AI will progress rapidly in both scientific discovery and technology commercialization. This is currently creating new materials and preserving data privacy. DALL-E may have arrived well ahead of schedule.
- Ubiquitous and Transparent Security. Within three to six years, “homomorphic encryption will be a cryptographic method that returns an encrypted result to the data owner. Essentially, this enables third parties to process encrypted data while not know the data or the results. Pioneers of homomorphic encryption understand that the future of this technology is tied to the increasing role of open innovation investments, which runs counter to the secrecy and silo mentality of traditional corporate research labs.” Think: OpenAI.
- Critical Enablers. Within three to six years, graph technologies will include data management and analytics techniques. This group of technologies enables the exploration of relationships between organizations, people, or transactions. Graph analytics consists of models that determine the “connectedness” across data points. These technologies can enhance the identification of influencers and communities in social media networks by evaluating when different paths spread behavior through unexpected community members. Graph databases are ideal for storing, manipulating, and analyzing the widely varied perspectives in the graph model due to their graph-specific processing languages and capabilities, scalability, and computational power.
The Future is Now
Emerging technologies offer a dream of a rich, enhanced version of life as we know it … or prefer it to be. If we had to move into the virtual realm out of necessity (because of a complete dystopian breakdown in our society), that’s a brutal possibility. Technological opportunities offer promise and when fully realized will enhance human capability. As we march down the road to high-tech ubiquity, we need to walk before we run. In terms of organizational transformation, technologies need to be considered based on their potential to enable operations, relationships with customers, and how a workforce is made more productive. Critical thinking is a tool to evaluate if the promise of tech applications will translate to real-world applications.
Our position is to be sure you balance the idealization of technology with its reality. The human factor is the key to the successful adoption of a technology foundation, and people need to be comfortable with tech and understand its role in the organization. Whether it’s working in a version of a meta office, operating hand in hand with AI or bots, or adopting O2O systems to build workforce communities, our inter-dependence on technology is on an irreversible course shaping the future.
As a final note, in some circles there is opinion that we are living a simulation. Like Douglas Adams described in Hitchhiker’s Guide to the Galaxy, someone is playing a massive digital game, and we’re the actors. But think about this: a simulation simulates an exact set of circumstances. It is beyond us to think that someone else is writing this article as we are at this exact moment. What’s the purpose in that? What’s even the fun? Simulation, to us, is more fantasy than fact, and is not what it seems to its fanbase.
Get “The Truth about Transformation”
The 2040 construct to change and transformation. What’s the biggest reason organizations fail? They don’t honor, respect, and acknowledge the human factor. We have compiled a playbook for organizations of all sizes to consider all the elements that comprise change and we have included some provocative case studies that illustrate how transformation can quickly derail.