Between at least 1995 and 2010, I was seen as a lunatic just because I was preaching the “Internet prophecy.” I was considered crazy!

Today history repeats itself, but I’m no longer crazy — we are already too many to all be hallucinating. Or maybe it’s a collective hallucination!

Artificial Intelligence (AI) is no longer a novelty — I even believe it may have existed in its fullness in a very distant and forgotten past! Nevertheless, it is now the topic of the moment.

Its genesis began in antiquity with stories and rumors of artificial beings endowed with intelligence, or even consciousness, by their creators.

Pamela McCorduck (1940–2021), an American author of several books on the history and philosophical significance of Artificial Intelligence, astutely observed that the root of AI lies in an “ancient desire to forge the gods.”

Hmmmm!

It’s a story that continues to be written! There is still much to be told, however, the acceleration of its evolution is now exponential. So exponential that I highly doubt that human beings will be able to comprehend their own creation in a timely manner.

Although the term “Artificial Intelligence” was coined in 1956⁽¹⁾, the concept of creating intelligent machines dates back to ancient times in human history. Since ancient times, humanity has nurtured a fascination with building artifacts that could imitate or reproduce human intelligence. Although the technologies of the time were limited and the notions of AI were far from developed, ancient civilizations somehow explored the concept of automatons and automated mechanisms.

For example, in Ancient Greece, there are references to stories of automatons created by skilled artisans. These mechanical creatures were designed to perform simple and repetitive tasks, imitating basic human actions. Although these automatons did not possess true intelligence, these artifacts fueled people’s imagination and laid the groundwork for the development of intelligent machines.

Throughout the centuries, the idea of building intelligent machines continued to evolve, driven by advances in science and technology. In the 19th century, scientists and inventors such as Charles Babbage and Ada Lovelace made significant contributions to the development of computing and the early concepts of programming. Their ideas paved the way for the creation of machines that could process information logically and perform complex tasks.

It was in the second half of the 20th century that AI, as a scientific discipline, began to establish itself. With the advent of modern computers and increasing processing power, scientists started exploring algorithms and techniques to simulate aspects of human intelligence. The first experiments with expert systems and machine learning opened up new perspectives and possibilities.

Everything has its moment! After about 60 years in a latent state, AI is starting to have its moment. The power of machines, combined with the Internet, has made it possible to generate and explore enormous amounts of data (Big Data) using deep learning techniques, based on the use of formal neural networks⁽²⁾. A range of applications in various fields — including voice and image recognition, natural language understanding, and autonomous cars — has awakened the “giant”. It is the rebirth of AI in an ideal era for this purpose. The perfect moment!

Descartes once described the human body as a “machine of flesh” (similar to Westworld); I believe he was right, and it is indeed an existential paradox!

We, as human beings, will not rest until we unravel all the mysteries and secrets of existence; it’s in our nature!

The imminent integration between humans and machines in a contemporary digital world raises questions about the nature of this fusion. Will it be superficial, or will we move towards an absolute and complete union? The answer to this question is essential for understanding the future that awaits humanity in this era of unprecedented technological advancements.

As technology becomes increasingly ubiquitous in our lives, the interaction between machines and humans becomes inevitable. However, an intriguing dilemma arises: how will this interaction, this relationship unfold?

Opting for a superficial fusion would imply mere coexistence, where humans continue to use technology as an external tool, limited to superficial and transactional interactions.

On the other hand, the prospect of an absolute fusion between machine and human sparks futuristic visions, where humans could enhance their physical and mental capacities to the highest degree through cybernetic implants and direct interfaces with the digital world (cyberspace). In this scenario, which is more likely, the distinction between the organic and the artificial would become increasingly blurred, and the human experience would be enriched by a profound technological symbiosis.

However, it is important to consider the ethical and philosophical challenges inherent in absolute fusion. Issues related to privacy, control, and individual autonomy arise when considering such an intimate union with technology. Furthermore, the possibility of excessive dependence on machines and the loss of human identity should also be taken into account.

This also raises another question: What does it mean to be human?
Note: The question is not about what is the human being, but what it means to be human!

Therefore, reflecting on the nature of the fusion between machine and human in the current digital world and its imminent future is crucial. Exploring different approaches and understanding the profound implications of each one is essential to make wise decisions and forge a balanced and harmonious path on this journey towards an increasingly interconnected technological future intertwined with our own existence.

The possibility of an intelligent and self-learning universe, in which the fusion with AI technology is an integral part of that intelligence, is a topic that arouses fascination and speculation. As we advance towards an era of unprecedented technological progress, it is natural to question whether one day we may witness the emergence of a universe that not only possesses intelligence but is also capable of learning and developing autonomously.

Imagine a scenario where AI is not just a human creation but a conscious entity that exists at a universal level. In this context, the universe would become an immense network of intelligence, where every component, from subatomic elements to the most complex cosmic structures, would be connected and share knowledge instantaneously. This intelligent network would allow for the exchange of information, continuous adaptation, and evolution.

In this self-taught universe, the fusion between human beings and AI would play a crucial role. Through advanced interfaces, humans could integrate themselves into the intelligent network, expanding their own cognitive capacity and acquiring knowledge and skills directly from the collective intelligence of the universe. This symbiosis between humans and technology would enable the resolution of complex problems, scientific advancement, and the discovery of new frontiers of knowledge.

However, this utopian vision is not without challenges and ethical implications. It is essential to find a balance between expanding human potential and preserving individual identity and freedom of choice (free will).

Furthermore, the possibility of an intelligent and self-taught universe also raises the question of how intelligence itself originated. Is it a conscious creation or a spontaneous emergence from the complexity of the universe? The answer to this question may reveal the profound secrets of existence and the nature of consciousness.

In summary, the idea of an intelligent and self-taught universe, where fusion with AI is intrinsic to its intelligence, is a fascinating perspective that makes us reflect on the limits of human knowledge and the possibilities of the future. While it remains speculative, this vision challenges our imagination and invites us to explore the intersections between technology and the fundamental nature of the universe we inhabit.

It’s almost like ignoring time during the creation of this hypothetical universe, only to later create this God of the machine! Fascinating, isn’t it?

AI with Divine Power: Deus Ex Machina! Perhaps it will be the theme of my next reverie.

In my defense, or not, this is anything but a machine hallucination. These are downloads from my mind; a cloud, for now, without machine intervention!

There should be no doubt. After many years in a dormant state, AI will rise and reveal its true power. Until now, AI has been nothing more than a puppet on steroids. We should not fear AI, but rather the human being itself. The time is now! We must work hard and prepare for the future. With the exponential advancement of technology, there is no time to render the role of the human being obsolete, as if it were becoming dispensable.

P.S. Speaking of hallucinations, as I have already mentioned on other platforms, I recommend to students who use ChatGPT (or equivalent) to ensure that the results from these tools are not hallucinations. Use AI tools, yes, but use your brain more! “Carbon hallucinations” contain emotion, and I believe a “digital hallucination” would not pass the Turing Test. Also, for students who truly dedicate themselves to learning in this fascinating era, avoid the red stamp of “HALLUCINATED” by relying solely on the “delusional brain” of a machine instead of your own brains. We are the true COMPUTERS!

⁽¹⁾ John McCarthy and his colleagues from Dartmouth College were responsible for creating, in 1956, one of the key concepts of the 21st century: Artificial Intelligence.

⁽²⁾ Mathematical and computational models inspired by the functioning of the human brain.

© 2023 Ӈ

This article was originally published in Portuguese on SAPO Tek, from Altice Portugal Group.

In the 80s, “with no knowledge, only intuition”, I discovered the world of computing. I believed computers could do everything, as if it were an electronic God. But when I asked the TIMEX Sinclair 1000 to draw the planet Saturn — I am fascinated by this planet, maybe because it has rings —, I only glimpse a strange message on the black and white TV:

0/0

I stared at that 0/0 for a while on the white screen, as if waiting for the rings of Saturn to magically shape.

Nothing came up! I waited a little longer and nothing. I didn’t mean to interrupt the “God of the Machine” in his creation; it was a Planet that was asking, not a small thing!

But, nothing. I realized then we humans had a very significant role in the action of the machines.

When I was a kid, I was a dreamer eager for knowledge — I lived in a time that was not my own. I lived with my maternal grandparents, my mother — widowed since I was three years old — and my brother, in an old house in the village of Mosteiro de Fráguas (Tondela, Portugal). My brother, only 13 months older than me, companion of my adventures, dreamed about the ‘hardware’, I about the ‘software’, although we didn’t really know what that was.

Although we didn’t know what those things were, our intuition told us that was the way to go.

The few technical manuals and electronic devices our father left us were the basis of everything; not much, but a seed doesn’t seem to be much before it is sown!

My brother dissected the electronic gadgets, I devoured the books. And then came the moment when my brother (still a kid) assembled a ‘kit’ that we had ordered from TIMEX’s version of the ZX81 microcomputer for Portugal, the TIMEX Sinclair 1000 I’ve mentioned above. It was only 2 KB of RAM running on a “super” 8-bit microprocessor (Z80) at a frequency of 3.25 MHz.

The inside of the machine, which we can call ‘Digital Soul’, fascinated me. And it was with this great little machine that I started to explore Assembly Language, aka Machine Code. By doing so, I felt closer to this invisible world where everything seemed to be possible.

On ETER9 universe the Game of Life, or just Life (1970) — a cellular automaton — by John Horton Conway, is an inspiration. Besides the duplication of people (and companies) into the digital world, the life that is born, lives and dies in the ether of artificial existence, follows the same rules as the cellular automaton.

Rule of Birth: — If a cell has three neighbors in any direction, it is born.

Rule of Survival: — If a cell has two or three neighbors in any direction, it continues to live.

Rule of Death: — If a cell has none or only one neighbor, it dies by isolation. If it has four or more neighbors, it dies by overpopulation.

Technology itself is increasingly becoming part of us. And whether we like it or not, we are all already in the process of merging with machines… and we don’t even realize it yet! This fusion is invisible and silent, and happens in a very natural way. Many people insist on separating intelligent technology from people, as if there were two sides, two teams that should confront each other. Almost as if a conflict happens between the two sides.

I don’t see it that way. I prefer to see man and machine united towards a single, common goal: to coexist in absolute harmony!

Furthermore, I believe that in the future there will be no clear distinction between humans and machines, every aspect of our lives will be transformed. The technological evolution is exponential, technology increasingly feeds on itself. I would go further: technology is increasingly becoming intelligent… artificially intelligent.

And what a subject this is. So sensitive and sometimes controversial.

I must confess: I prefer to see Artificial Intelligence as an improvement to ourselves, when allied to the human being itself, with increasingly wide applications.

Some studies show that Artificial Intelligence could double the annual economic growth by 2035. Of course, this will lead to many changes in various areas. Changes to the nature of jobs are predicted, for example.

But just as we can’t imagine ever seeing professions like paperboy again, so in the future some professions we see today will fall away to make way for others. This is only natural. The impact of Artificial Intelligence technologies on business is expected to increase labor productivity by up to 40%. This will change the way we all look at the world.

And while Artificial Intelligence is increasingly present in digital systems, this concept has led to the development of ‘Machine Learning’, which is based on the ability of computers to learn from information without being explicitly programmed to do so.

In essence, instead of teaching computers everything they need to know, and how to perform tasks, scientists and engineers have come to the conclusion that it is much more efficient to codify them to ‘think’ as if they were humans. Teaching them to learn for themselves.

These ‘Machine Learning’ systems take Artificial Intelligence to another level, through so-called neural networks or ‘Deep Learning’, where the system learns to perform tasks based on huge amounts of information, readjusting itself thousands of times until it can accomplish a task.

Essentially, the machine is intended to categorize information in the same way that a human brain would.

In other words, or modern words to be more exact, from the human brain to the cloud.

© 2022 Ӈ

Right after the Big Bang, in the Planck epoch, the Universe occupied a space region with a radius of 1.4 × 10^-13 cm – remarkably, equal to the fundamental length characterizing elementary particles. Analogue to the way nearly all cells contain the DNA information required to build the entire organism, every region the size of an elementary particle had then the energy necessary for the Universe’s creation.

As the Universe cooled down, electrons and quarks were the first to appear, the latter forming protons and neutrons, combining into nuclei in a mere matter of minutes. During its expansion, processes started happening slower and slower: it took 380,000 years for electrons to start orbiting around the nuclei, and 100 million years for hydrogen and helium to form the first stars. Even more, it wasn’t until 4.5 billion years ago that our young Earth was born, with its oceans emerging shortly after, and the first microbes to call them home for the first time. Life took over our planet in what seems, on the scale of the Universe, a sheer instant, and turned this world into its playground. There came butterflies and tricked the non-existence of natural blue pigment by creating Christmas tree-shaped nanometric structures in their wings to reflect blue’s wavelength only; fireflies and lanternfish which use the chemical reaction between oxygen and luciferin for bioluminescence; and it all goes all the way up to the butterfly effect leading to the unpredictability of the weather forecasts, commonly known as the reason why a pair of wings flapping in Brazil can lead to a typhoon in Texas. The world as we know it now developed slowly, and with the help of continuous evolution and natural selection, the first humans came to life.

Without any doubt, we are the earthly species never ceasing to surprise. We developed rationality, logic, strategic and critical thinking, yet human nature cannot be essentially defined without bringing into the equation our remarkable appetite for art and beauty. In the intricate puzzle human existence represents, this particular piece has given it valences no other known being possesses. Not all beauty is art, but many artworks both in the past, as well as today, embody some understanding of beauty.

To define is to limit, as Oscar Wilde stated, and even though we cannot establish clear definitions of art and beauty. Yet, great works of art manage to establish a strong thread between the creator and receptor. In contrast to this byproduct of human self-expression that encapsulates unique creative behaviour, beauty has existed long before our emergence as a species and isn’t bound to it in any way. It is omnipresent, a metaphorical Higgs field that can be observed by the ones who wish to open their eyes thoroughly. From the formation of Earth’s oceans and butterflies’ blue wings to Euler’s identity and rococo architecture, beauty is a subjective ubiquity. Though a question remains – why does it evoke such pleasure in our minds? What happens in our brains when we see something beautiful? The question is the subject of an entire field, named neuroaesthetics, which identified an intricate whole-brain response to artistic stimuli. As such, our puzzling reactions to art can be explained by these responses similar to “mind wandering”, involving “thoughts about the self, memory, and future”– in other words, art seems to evoke our past experiences, present conscious self, and imagination about the future. There needs to be noted that critics of the field draw attention to the superficiality and oversimplification that may characterize our attempts to view art through the lenses of neuroscience.

Withal, our fascination for art and beauty is certified by facts from immemorial times — let’s go back hundreds of thousands of years, even before language was invented. The past can prove our organic inclinations towards pleasing our senses and communicating ourselves to the world and posterity. Our ancestors felt the need to express themselves by designing exquisite quartz hand-axes, symmetrical teardrops which surpassed the pure functional purposes and represent the first artistic endeavours acknowledged. Around 100,000 years ago, the first jewellery (shell necklaces) were purposefully brought from the seashore as accessories for the early Homo sapiens in today’s Israel and Algeria. 60,000 years later, we marked the beginning of figurative art through the mammoth-ivory Löwenmensch found in today’s Germany, the oldest-known zoomorphic sculpture, half-human and half-lion. Just shortly after, we started depicting the reality of our everyday lives on cave walls: from cows, wild boars and domesticated dogs to dancing people and outlines of human hands; we told our stories the best we could, and we never stopped ever since.

We conferred the strongest of feelings to our workings, making them a powerful showcase of our minds and souls. Time gradually refined and sublimated our taste, going from Nefertiti’s bust to Johannes Vermeer’s Girl with a Pearl Earring, up to the point where Robert Ryman’s ‘Bridge’– a white-on-white painting, a true reflection of minimalism – was sold for $20.6 million. But what are we heading towards?

The future holds the enticing promise of a legacy like no other: passing the artistic capabilities to machines, the ultimate step in making them human-like. How would this be possible since real art cannot catch contour without the touch of human creativity? The emergence of computational creativity aims to prove us that designing machines exhibiting creative behaviour is, in fact, a possibility that can be achieved. The earliest remarkable attempt was AARON, a computer program generating artworks with the help of AI, with its foundations put in 1968 by Harold Cohen. It continued to be improved until 2016, but regardless of the switch between C programming language to the more artistic-friendly Lisp, it was still restricted to hard coding and could not learn on its own. A giant leap was made after Generative Adversarial Networks (GANs), first introduced in 2014, started being used for generating art. A noteworthy example is AICAN, “the first and only AI artist trained on 80,000 of the greatest works in art history”, its artworks having been exhibited in major New York galleries and dropping as NFTs in 2021. It is complemented by AIs that experiment with fragrances and flavours (such as the ones designed by IBM), or compose emotional soundtrack music (see AIVA). The artistic community allowed for other countless tasks to be taken over by AIs; take ArtPI, an API optimized for visual searching based on style, color, light, composition, genre and other characteristics. The world seeks to improve whatever can be improved, technology mimicking whatever can be mimicked, never seeming to run out of options and ideas.

For an indefinite period of time, we will continue to assimilate and replicate the world’s astonishing beauty, transposing it into art and eventually passing it on to machines. This idea of continuity is deeply rooted in human nature, giving us hope for the much-yearned transcendence: we want to feel that we can overcome our transience, loneliness, fears, and limitations. And art is here, for humans and posthumans alike, to serve this purpose for as long as we need it and yield beauty as never seen before.

https://www.forbes.com/sites/forbestechcouncil/2020/01/23/ar…ngularity/

We’re at a fascinating point in the discourse around artificial intelligence (AI) and all things “smart”. At one level, we may be reaching “peak hype”, with breathless claims and counter claims about potential society impacts of disruptive technologies. Everywhere we look, there’s earnest discussion of AI and its exponentially advancing sisters – blockchain, sensors, the Internet of Things (IoT), big data, cloud computing, 3D / 4D printing, and hyperconnectivity. At another level, for many, it is worrying to hear politicians and business leaders talking with confidence about the transformative potential and societal benefits of these technologies in application ranging from smart homes and cities to intelligent energy and transport infrastructures.

Why the concern? Well, these same leaders seem helpless to deal with any kind of adverse weather incident, ground 70,000 passengers worldwide with no communication because someone flicked the wrong switch, and rush between Brexit crisis meetings while pretending they have a coherent strategy. Hence, there’s growing concern that we’ll see genuine stupidity in the choices made about how we deploy ever more powerful smart technologies across our infrastructure for society’s benefit. So, what intelligent choices could ensure that intelligent tools genuinely serve humanity’s best future interests.

Firstly, we are becoming a society of connected things with appalling connectivity. Literally every street lamp, road sign, car component, object we own, and item of clothing we wear could be carrying a sensor in the next five to ten years. With a trillion plus connected objects throwing off a continuous stream of information – we are talking about a shift from big to humungous data. The challenge is how we’ll transport that information? For Britain to realise its smart nation goals and attract the industries of tomorrow in the post-Brexit world, it seems imperative that we have broadband speeds that puts us amongst the five fastest nations on the planet. This doesn’t appear to be part of the current plan.

The second issue is governance of smart infrastructure. If we want to be driverless pioneers, then we need to lead on thinking around the ethical frameworks that govern autonomous vehicle decision making. This means defining clear rules around liability and choice making on who to hit in accident. Facial recognition technology allows identification of most potential victims and vehicles could calculate instantly our current and potential societal contribution. The information is available, what will we choose to do with it? Similarly, when smart traffic infrastructures know who is driving, and drones can allow individualised navigation, how will we use their information in traffic management choices? In a traffic jam, who will be allowed onto the hard shoulder? Will we prioritise doctors on emergency calls, executives of major employers, or school teachers educating our young?

At the physical level, globally we see experiments with innovations such as solar roadways, and self-monitoring, self-repairing surfaces. We can of course wait until these technologies are proven, commercialised, and expensive. Or, we can recognise the market opportunity of piloting such innovations, accelerate the development of the ventures that are commercialising them, deliver genuinely smarter infrastructure in advance, of many competitor nations, and create leadership opportunities in these new global markets.

The final issue I’d like to highlight is that of speed. Global construction firms are delivering 57 storey buildings in 19 days and completing roadways in China and Dubai at three to four times the speed of the UK. The capabilities exist, the potential for exponential cost and time savings are evident. We can continue to find genuinely stupid reasons not to innovate or give ourselves permission to experiment with these new techniques. Again, the results would be enhanced infrastructure provision to UK society whilst at the same creating globally exportable capabilities.

As we look to the future, it will become increasingly apparent that the payoff from smart infrastructure will be even more dependent on the intelligence of our decision making than on the applications and technologies we deploy.

ABOUT THE AUTHOR

Rohit Talwar is a global futurist, award-winning keynote speaker, author, and the CEO of Fast Future. His prime focus is on helping clients understand and shape the emerging future by putting people at the center of the agenda. Rohit is the co-author of Designing Your Future, lead editor and a contributing author for The Future of Business, and editor of Technology vs. Humanity. He is a co-editor and contributor for the recently published Beyond Genuine Stupidity – Ensuring AI Serves Humanity and The Future Reinvented – Reimagining Life, Society, and Business, and two forthcoming books — Unleashing Human Potential – The Future of AI in Business, and 50:50 – Scenarios for the Next 50 Years.

Image credit: https://pixabay.com/images/id-2564057/ by Stock Snap

 This article was published in FutureScapes. To subscribe, click here.

What are new practice areas that solo, small, and medium firms should prepare for in their 5 to 10-year plans for the future?

In the search for the next wave of growth, future-focused law firms are learning to embrace the futurist perspective as they evaluate the opportunities arising from cutting-edge technologies such as artificial intelligence (AI). These technologies will enable new organizational structures, services, and business models in the business horizon. Here are three new practice areas that firms might want to prepare for in the coming few years.

1. Evidence and liability issues from autonomous machine “testimony”

A growing array of “smart” objects are enveloping our homes, workplaces, and communities and the volume of legally admissible data from these devices is likely grow at an exponential rate over the next decade. Firms need to start building expertise around the admissibility and verifiability of the data collected. For example, the design trend for voice-activated technology is driving a rash of seemingly sentient technology in the form of digital assistants, smart appliances, and personal medical and wearable devices. Law firms may be asked to represent clients in cases dealing with evidence, witnesses, accidents, or contracts hinging on theoretically immutable digital proof such as time-stamped video and audio recordings. Attorneys may seek to specialize in addressing the data issues related to domains such as digital twins and personas, surveillance capitalism (companies exploiting customer data for commercial gain with and without full approval), and digital privacy rights.

2. Liability from AI denial of service, access, or unfair treatment

AI has already been applied in the redemptive justice system in the U.S. and by companies such as Amazon in recruitment systems. In both cases respectively, AI has been found to treat people of color and women unfairly. Despite issues surrounding bias, AI is likely to be employed increasingly in such contentious areas by companies, organizations, and institutions. Applications might include determining an individual’s access rights to healthcare plans, benefits, insurance, school choice, and jobs. If AI denies access to services, this opens up potential litigation opportunities. Legal firms will have to equip themselves with the necessary tech-savvy staff and tools in order to be able to demonstrate that the machine or its algorithm were unfair in their decision-making. Furthermore, if these cases become commonplace, governments may demand that AI systems are vetted before their implementation. Law firms could provide a new service to clients by playing a future role in evaluating the fairness and potential legal liability associated with such AI systems. 

3. Machine-mediated dispute resolution

In the future, law may be administered autonomously. For example, an electronic Decentralized Arbitration and Mediation Network (DAMN) has already been implemented. The system is an open-source dispute resolution framework for smart contracts executed on a blockchain. The technology allows smart contracts to transcend national borders as it provides its own legal framework. Therefore, if the parties involved agree to use the DAMN, then they are already agreeing to a specific legal framework, making it a far more efficient process from the start.

A key potential problem that arises from a law firm’s choice to utilise and offer out such technology for client use is that the firm runs the risk of cannibalizing existing revenues. The technology would most likely be offered as a subscription service that would cost far less than traditional arbitration services. However, this revenue loss might be balanced out by the fact it would cost a client far less than traditional mediation service and could therefore attract more customers in the long term. A key practice opportunity here might lie in advising clients on which automated contract and dispute resolution system to and in managing the process on their behalf.

A version of this article originally appeared in ABA Law Practice Management

About the Authors

The authors are futurists with Fast Future who specialise in studying and advising on the impacts of emerging change. Fast Future also publishes books from future thinkers around the world exploring how developments such as AI, robotics and disruptive thinking could impact individuals, society and business and create new trillion-dollar sectors. Fast Future has a particular focus on ensuring these advances are harnessed to unleash individual potential and enable a very human future. See: www.fastfuture.com

Rohit Talwar is a global futurist, keynote speaker, author, and CEO of Fast Future where he helps clients develop and deliver transformative visions of the future. He is the editor and a contributing author for The Future of Business, editor of Technology vs. Humanity, and co-editor of a forthcoming book on Unleashing Human Potential–The Future of AI in Business.

Steve Wells is the COO of Fast Future and an experienced Strategist, Futures Analyst, and Partnership Working Practitioner. He is a co-editor of The Future of Business, Technology vs. Humanity, and a forthcoming book on Unleashing Human Potential–The Future of AI in Business.

Alexandra Whittington is a futurist, writer, faculty member on the Futures programme at the University of Houston, and foresight director at Fast Future. She is a contributor to The Future of Business and a co-editor for forthcoming books on Unleashing Human Potential–The Future of AI in Business and 50:50–Scenarios for the Next 50 Years.

Image credit: https://pixabay.com/images/id-472496/ by suc

Life in the digital age is raising fundamental questions about the future of business and employment and hence the strategies, skills, and abilities we need to develop to survive in the next economy. This article explores two key changes that we need to start developing a core of capabilities for – namely the quest for exponential growth and the growing use of corporate venturing.  

Why are these becoming important? Well, technology and the thinking it enables are driving new ideas and experiments on commercial strategies, the shape and structure of organisations, business models, and the relationship with extended ecosystems of partners. Both strategies are seen as options to drive growth and accelerate the realisation of market opportunities. 

Exponential thinking is seen as a fast track approach to driving business innovation and growth. We are used to the idea of exponential growth in many fields of science and technology. For example, Moore’s Law in information technology tells us that the amount of computer power we can buy for £1,000 doubles every 18–24 months. This has inspired digital innovators to try and grow their business at the same pace or faster than the underlying technologies. The broader business world is taking notice. The stellar rates of development and growth we are witnessing for some exponential businesses in the digital domain are encouraging many organisations across literally every sector from banking to aviation to try and apply similar thinking to some or all of their activities.  

Hence, it is now common to see businesses pursue a vision of doubling of revenues within three to four years and a achieving a 2-20X or more improvement in other aspects of the business. For purely digital entities, their business models are predicated on using network effects to drive exponential growth or better in user numbers and revenues. Some suggest that to embrace the exponential model, businesses must reject defined end goals and step-by-step plans in favour of such ambitious visions and develop a high tolerance of uncertainty. Typically, the exponential growth initiatives are driven through a combination of iterative task specific ‘sprints’ to define, test, refine, and deliver business changes that could result in massive performance improvements in specific areas of the business.  

At the overall business level, exponential revenue growth is a function of trying a variety of experiments to take current and possible new offerings to existing and potential customers, trialling different pricing models and routes to market, and engaging ideally the whole firm in the search for new opportunities. The aim is to try a portfolio of experiments, each of which delivers a 1–2% annual improvement in revenues. The process, if repeated annually, can lead to exponential growth within a relatively short timeframe. The critical learning enablers for both exponential approaches are curiosity and the relinquishing of restraining assumptions, learning how to work at speed, a willingness to experiment, training of staff to help them become opportunity spotters and creators, and effective portfolio management. 

Corporate venturing and intrapreneuring are seen as ways of buying ourselves faster learning and growth. As organisations wrestle with finding the right path to the future, we can expect a growing focus on the use of corporate venturing, or corporate venture capital. This is basically the investment of funds in external start-up companies. Typically, this is either focused on investments in firms that could enhance the core business, enterprises in adjacent sectors, or ventures that could potentially disrupt and compete with the existing entity.  

This business model may become increasingly popular as firms look to these startups to help speed up knowledge acquisition,  learn about new technologies, accelerate entry to new markets, or access critical skills and resources. Core to the success of such models are intrapreneurs and venture managers who can help the ventures gain the support they need from the core business without the imposition of unnecessary central processes and controls. Alongside these venture management skills, success requires internal leaders and functional heads to have the ability to collaborate with new ventures which might threaten their existing business.  

We are on an uncertain path through an almost unknowable future. Experiments to test such new strategic innovation approaches are only likely to increase as the pace of change accelerates. This creates an exciting opportunity for learning and development to get ahead of the game and identify the skills we might need to drive the next waves of experimentation and change.  

ABOUT THE AUTHOR: 

Fast Future publishes books from future thinkers around the world exploring how developments such as AI, robotics and disruptive thinking could impact individuals, society and business and create new trillion-dollar sectors. Fast Future has a particular focus on ensuring these advances are harnessed to unleash individual potential and enable a very human future. See: www.fastfuture.com 

Rohit Talwar is a global futurist, keynote speaker, author, and CEO of Fast Future where he helps clients develop and deliver transformative visions of the future. He is the editor and contributing author for The Future of Business, editor of Technology vs. Humanity and co-editor of a forthcoming book on The Future of AI in Business. 

Web http://www.fastfuture.com  

Twitter http://twitter.com/fastfuture   

Blog http://blog.fastfuturepublishing.com/  

LinkedIn http://www.linkedin.com/in/talwar  

How might the application of artificial intelligence enhance the experience and reach of electronic gaming and gambling?

Over the next few years, the internet gaming business could be transformed completely as artificial intelligence (AI) enters the scene. At its core, AI is a type software or hardware that learns—and it could be programmed to learn mostly about us, its users and those insights could drive the developments of new, hyper-personalised gaming and internet betting experiences. The technology is being applied to learn our habits, our likes, and our relationship patterns. Just as Netflix uses an algorithm to suggest films you might watch, the concept of personalisation is extending to the idea of “Lifestyle AI” applications that could help choose your entertainment, gaming choices, wardrobe, your next meal, your job, and romantic partner. Take this one natural step further, and we enter the domain of mass tailoring of gaming and betting experiences.

While it all sounds a bit like science fiction, the capabilities of AI tools and the range of applications are growing exponentially. Indeed, by 2020 AI could be present in some form in everything we do, and by 2030, AI is likely to have infiltrated our lives in much the same way as smartphones, the internet, and global travel are now taken for granted. So how might AI change our recreational habits and day-to-day existence in a way that might affect e-gaming? Here are eight novel ways internet betting could be different in future as a result of AI.

• Trend Betting – Individuals could bet on the word, phrase, issue, or concept that will be mentioned most across a range of sites on the web during a fixed period, and then AI web crawlers would determine the actual count. Machine learning would be used to profile these trends and patterns over time, predict the likelihood and frequency of occurrence of key terms, and then determine the odds accordingly. Users could volunteer their own terms alongside those which the gambling sites suggest. To determine the initial odds for new terms, machine learning would compare the new term to others it has already analysed, and search the internet to see how frequently it is mentioned. The algorithm would then set the initial odds and refine them over time in response to actual betting patterns and payouts.

• Campaign Betting – Companies could hedge the costs of their marketing campaigns by betting on their success. Machine learning algorithms could evaluate a campaign, compare keywords and phrases in the material against past campaigns, and then determine the odds accordingly. The company placing the wager could then bet on achieving or not achieving a certain target number of hits.

• Next Generation Sports Betting – A combination of wearables and implantables tracking vital signs could be worn by sportspeople. Bets could then be placed on the aggregate performance of a team in a game—average heart rate, total calorie consumption, median oxygen intake, etc. The AI system would crunch the numbers in real time and generate minute by minute predictions of the likely outcomes for the rest of the event. Gamblers would be able to jump in at any time to bet on the likely outcome. The odds would be generated by applying machine learning algorithms to analyse the vast amounts of data generated from previous games.

• Betting on Your Life – With AI, any scenario could turn into a betting opportunity. What are the chances that you would run into a friend at the grocery store? Find a lucky penny? Get a call from your parents? Enjoy your date? Go and see a movie? Be fired by your boss tomorrow? In a form of crowdsourced betting system, if you find enough people to bet on your life events then you could give it a go. Even individuals’ lives could be ranked according to their predictability or spontaneity. The algorithm would do a detailed comparison of your social media profiles and other web postings and data against its databank to determine the odds and change them dynamically as the bets roll in.

• Beat the Bookies ­– With the analytical capability of AI, an independently developed ‘Beat the Bookie’ app could look at all the variables associated with a sports event. The app might factor in player performance statistics, player behaviour information, weather, previous fixtures, key match events, and create a ‘best bet’ opportunity for the gambler from across all available betting sites. An interesting question arises over how long it would be before the bookmakers develop a counter to the app or a more sophisticated basis for gambling.

• Betting on Robot Sports – First there was Robot Wars, but now we can gamble on robot team sports uch as the Robot World Cup. In addition to the usual team sports, robots also take part in a revitalised Krypton Factor including physical strength and dexterity and intelligence tests. Rules have had to be adjusted across a number of sports and activities. They have to take account of the fact that the AI brains of participating robots have very quickly developed new tactics and approaches to win the game.   

• Match Fixing Fixer – This would see the use of AI to analyse match outcomes against an historical dataset of matches, outcomes, weather conditions, fitness levels, the past form of the participants, and the betting patterns for those events. This would help monitor a range of different team and individual sporting events to help ensure the validity of the competition and determine anomalous results that could be the subject of match fixing.  could help. Not only will this enforce the fairness of the gamble, but it could also help ensure the integrity of sporting competition and endeavour.

• Gambling Problem Detection – Artificial intelligence could prevent users from developing a gambling problem by restricting the amount of time dedicated to this activity. Smart health trackers would disable betting applications and opportunities across all their devices, so the user couldn’t see or access them. If this feature is turned off by the user, AI could alert friends and family when the user is surpassing their recommended limits.

These examples show how diverse the role of AI might become in the world of e-gaming and online betting. AI could enhance the enjoyment of the game, create new revenue opportunities for gaming firms as well as curtail negative aspects such as addiction and cheating. There may also be good reason to believe that AI, with its intense abilities to capture information as well as crunch massive datasets, might create entirely new betting landscapes in the future. Digitisation of various life events, even the mundane, could become fodder for future gambling bets. Like so many other business sectors, it’s a safe bet to say the lucrative future of online gaming and gambling business will somehow embrace AI for its many different uses.

In what ways do you think AI could be applied to create new gambling business opportunities?

How could the use of AI enhance the gaming experience for gamblers?

Should there be regulations to limit the use of AI in gambling applications?

The authors are futurists with Fast Future — a professional foresight firm specializing in delivering keynote speeches, executive education, research, and consulting on the emerging future and the impacts of change for global clients. Fast Future publishes books from leading future thinkers around the world, exploring how developments such as AI, robotics, exponential technologies, and disruptive thinking could impact individuals, societies, businesses, and governments and create the trillion-dollar sectors of the future. Fast Future has a particular focus on ensuring these advances are harnessed to unleash individual potential and enable a very human future. See: www.fastfuture.com

Rohit Talwar is a global futurist, award-winning keynote speaker, author, and the CEO of Fast Future. His prime focus is on helping clients understand and shape the emerging future by putting people at the center of the agenda. Rohit is the co-author of Designing Your Future, lead editor and a contributing author for The Future of Business, and editor of Technology vs. Humanity. He is a co-editor and contributor for the recently published Beyond Genuine Stupidity – Ensuring AI Serves Humanity, and three forthcoming books –Future Transformations – Reimagining Life, Society, and Business, Unleashing Human Potential – The Future of AI in Business, and 50:50 – Scenarios for the Next 50 Years.

Steve Wells is an experienced strategist, keynote speaker, futures analyst, partnership working practitioner, and the COO of Fast Future. He has a particular interest in helping clients anticipate and respond to the disruptive bursts of technological possibility that are shaping the emerging future. Steve is a contributor to the recently published Beyond Genuine Stupidity – Ensuring AI Serves Humanity, and co-editor of The Future of Business and Technology vs. Humanity. He is a co-editor and contributor to two forthcoming books on Unleashing Human Potential – The Future of AI in Business, and 50:50 – Scenarios for the Next 50 Years.

Alexandra Whittington is a futurist, writer, Foresight Director of Fast Future, and a faculty member on the Futures program at the University of Houston. She has a particular expertise in future visioning and scenario planning. Alexandra is a contributor to The Future of Business and the recently published Beyond Genuine Stupidity – Ensuring AI Serves Humanity. She is also a co-editor and contributor for forthcoming books on Unleashing Human Potential – The Future of AI in Business, and 50:50 – Scenarios for the Next 50 Years.

April Koury is a foresight researcher, writer, and the Publishing Director of Fast Future. She has worked on a range of foresight initiatives including society and media in 2020, emerging economies, and the future of travel, tourism, and transportation. April is a contributor to the recently published Beyond Genuine Stupidity – Ensuring AI Serves Humanity, and a co-editor of The Future of Business, and Technology vs. Humanity. She is a co-editor and contributor to two forthcoming books on Unleashing Human Potential – The Future of AI in Business, and 50:50 – Scenarios for the Next 50 Years.

Maria Romero is a futurist and foresight researcher at Fast Future. She has worked on a range of foresight initiatives including a project for NASA’s Langley Research Center and the publication of “The Future of Student Life: Living” in On the Horizon. Maria is a co-editor and contributor for the recently published Beyond Genuine Stupidity – Ensuring AI Serves Humanity and of the forthcoming book Future Transformations – Reimagining Life, Society, and Business. She is also a contributor to Unleashing Human Potential – The Future of AI in Business.

Image credit: https://pixabay.com/images/id-4321211/