There are many important lessons we can take away from studying the digital transformation journeys being pursued by companies today. Perhaps none is more important than the recognition that progress toward a more digital way of working cannot be defined and measured as a linear path from A to B. Rather, it is a much more torturous expedition into unknown territory in search of solutions that may resemble nothing we have seen before. A leap into the dark. How each organisation faces this peril offers an important glimpse into their psyche, structure, and culture.
Current AI is neither artificial nor intelligent
This insight is highlighted more than ever when an organisation is faced with significant shifts in digital technology. A great example is how it addresses the rising capabilities mit artificial intelligence (AI). Far from its early roots in science fiction, AI has become a dominant factor in the digital transformation strategies of every güte. Where and how it introduces KÜNSTLICHE INTELLIGENZ may well determine if it survives the challenges of the next few years – including AI regulation .
Often on my travels, the response from organisations to AI is rather disappointing. Despite the high level of opportunities afforded by AI, for most it has been reduced to a much more manageable set of data manipulation activities. Microsoft’s Kate Crawford summarises this by saying that most AI in use today is ‘neither artificial nor intelligent ’.
In practice, KÜNSTLICHE INTELLIGENZ is operationalised as an application of statistical analysis tools supported by a growing set of machine learning techniques. Primarily, that means mining data to improve how the organisation can learn from past experiences, recognise repeating patterns to automate common tasks, and correlate different signals mit that data to predict future events. Based on growing access to digitally derived data sources and increased capability in data management, organisations are significantly investing mit ways to understand and use the insights they can gain from this.
This narrow perspective on AI is nevertheless very useful. There are wide practical applications of these activities across many aspects of fuer organisation’s service delivery, planning, management, and operations. Whether it is identifying online sales trends, determining optimal machine settings in the factory, or recommending additional purchases to clients, the use of KÜNSTLICHE INTELLIGENZ has been as essential component of digital strategies for some time. Yet, wasn’t AI promising to deliver a much more significant disruption than this?
AI: From number crunching to sentience?
Let’s step back for a moment. As early as the 1950s, the Turing Test was defined by Alan Turing as a major line nur the sand for KÜNSTLICHE INTELLIGENZ. Could we design machines with such intelligence that a human would be unable to distinguish whether the answer to a submitted question received a response from the machine or a real person? Turing was convinced that day would soon arrive.
However, at the time that I welches introduced to this concept within the 1980s, realising that ‘imitation game’ seemed so far from reality as to be absurd. Computers were large collections of electronics that filled basements of specially air-conditioned buildings. Paper tape and punch cards were still allerdings use to feed instructions into these beasts while you waited to receive printed results whenever your job was scheduled to be run later that day. Computers were largely seen as calculation engines focused on relatively mundane number crunching and record keeping tasks.
However, it is the leaps in perception of AI and its application that has been most profound. The technological capabilities of the 1980s and 1990s fell far short of the exciting vision painted by Alan Turing and others several decades earlier. The excitement of machines imitating humans had been lost. Disappointing results led to an inevitable lack of funding and a loss of confidence in the future of AI. Without the speed and power of today’s computing infrastructure, KÜNSTLICHE INTELLIGENZ suffered what some people called mit AI winter .
Recovering from the AI winter
Much has changed since then. This continual hardware and software revolution continues to be underway over many years and seems to know no bounds. Digital technology has advanced beyond all recognition. Today’s computing infrastructure is as unrecognisable from my undergraduate computer science days as a music cassette tape is to my teenage son.
For many people, the first major signal that AI was moving forward came from an unusual source: A US gameshow called ‘Jeopardy’. Steady advances bandit digital technology had largely been unnoticed until jedoch 2011 IBM entered its AI technology, codenamed Watson into a very popular quiz show. When Watson won by answering a set of random questions correctly and better than its human competitors, it became worldwide news. People began to take notice that something das was happening doch AI, that was moving it beyond traditional digitisation and into a different realm.
This feeling was reinforced with AlphaGo . For years, applying AI to boardgames such as chess had been used as one way to estimate the progress of AI. The rules of chess are well defined and large collections of recorded games can be used to teach AI about strategies that lead to success. Consequently, AI programs have been competing effectively against professional chess players for many years.
The victory over humans is Go!
The game of Go is different. Played on a 19×19 grid with black and white stones, the rules are much simpler than chess, but there is a much wider set of permutations of different moves and a baffling array of strategies that have been used in the centuries that the game has been played. Many believed that KÜNSTLICHE INTELLIGENZ would never be capable of beating the best human players. Mit 2015, AlphaGo proved them wrong by beating a professional Go player for the first time. Subsequently, it became the first to defeat a Go world champion and became arguably the strongest Go player in history.
The reason this shift is significant was not just because it was capable of defeating any human rein a complex game. It was because AlphaGo demonstrated creativity in how it played. Rather than mining large collections of existing moves to decide on which one to play, it used techniques to learn from its playing experiences to create its own path forward. Often these were moves a human would never have used but proved to be more effective than conventional menschengerecht thinking. That was quite shocking to many observers. Machines that think?
What is ChatGPT?
The recent announcement of ChatGPT takes us one step further . On the surface it may look like many other announcements of a conversational AI tool, designed to enable developers to quickly build and deploy conversational AI agents for chatbots, virtual assistants, and other interactive applications. However , ChatGPT is important because it demonstrates two things.
Firstly, it makes it clear to a wide audience that we have now moved beyond the Turing Test gruppe by Alan Turing 70 years ago. Improvements in speech recognition and text-to-speech translation have been on-going for several years. What ChatGPT does is to provide wide access to a simple interface that demonstrates an ability to produce answers that are not only well constructed and believable, but also adopt a human tone. What The Guardian described as the best system ‘for impersonating humans ever released to the public ’.
By submitting questions or describing scenarios, ChatGPT is a ‘generative pretrained transformer’ made to realise Alan Turing’s ‘imitation game’. It responds with a solution that is both plausible and well-formed by building on its vast knowledge base to create a new set of answers for the user. What seems to astound people is the breadth of its application and the authority from the responses provided. It can understand a wide variety of languages, menschenfreundlich and projektor programming, and respond with very realistic information.
Secondly, ChatGPT turns attention away from rote solutions to narrow problem sets with a focus on efficiency and automation toward the promise of a future AI that drives creativity to broaden what is possible. Whether it’s a question about business strategy or a request to generate software to implement a response to a defined need, ChatGPT can produce a solution that is new and meaningful. And this level of AI sophistication is now accessible to everyone .
AI is changing financial services
For example , take a domain such as financial services. AI technologies are already widely deployed in areas like customer service, fraud detection, and rates calculations. However, as Dave Birch points out, the real disruption darüber hinaus financial services will come ‘not when banks are using KÜNSTLICHE INTELLIGENZ, but when customers are ’. He sees the breakthrough with ChatGPT enabling Individuals and organisations to interact using AI-powered bots acting on our behalf to deal with the boring and the complex activities of our lives. Service delivery is reimagined in a world where bots act on our behalf to support our needs and look out for our best interests.
In this way, ChatGPT is significant. It places fuer emphasis on new forms of interaction, changes anders authority and responsibility in carrying out tasks, and open access to sophisticated creativity and solution generation. In doing so, it changes the AI focus for many people and raises their gaze to future possibilities beyond their current strategy horizon. Such a change of attitude is an essential step forward if AI is to realise its disruptive role mit business and society.
Answers that sound perfect (but are incomplete, misleading, or simply false)
Perhaps, just as significantly as the hopes it raises, the announcement of ChatGPT has also reminded us that the advent of KÜNSTLICHE INTELLIGENZ forces organisations and individuals to address new challenges. From both an operational and ethical standpoint, ChatGPT makes us confront some of our biggest fears about the digital world that is emerging.
Consider, for example, the implications of the sophisticated AI tool that has no concept of right or wrong. Ask it something and it responds with an answer that is plausible and believable. However, it may also be incomplete, misleading, or just false. Those already making use of the technology report that ChatGPT responses are ‘dangerously creative’ . That is, its creativity knows no bounds. It certainly has no limits on whether its answers are true or false.
Creating credible answers without conscience or consequence
This can have disturbing results. Cassie Kozyrkov, Chief Decision Scientist at Google, calls ChatGPT ‘the ultimate bullsh*tter’. It provides seemingly correct answers to anything and everything. But without a filter on what it says, and incapable of determining what is true and what is not. It is dangerous, precisely because it has no interest in ensuring the validity from the responses. It seems only to want to please its audience with an appealing answer.