The Possibilities Of Data And Computing: 180 Years In The Making
It was the Ancient Greeks who created Antikythera, the first known analogue computer. For centuries since, the concept of automated computation has permeated civilisations across time, spurring innovation, and bringing us closer to the data and computing landscape of today.
Even in 1841, when Dun & Bradstreet was established, there was a demand for documenting important information in one place in order to support business decisions. Of course, at this point, data was noted and analysed in paper form, but making that collection and synthesis more organised and standardised was a critical step in the progression of today’s digital landscape. The purview this early data gave many businesses the ability to adapt to crises such as political turmoil and conflict – a principle that has remained a fundamental benefit throughout data and computing’s evolution.
You only need to look at the portfolios of some of the longest surviving brands to understand how the results of data and computing have manifested within our society. Highly prominent in this rare company is IBM, which started its journey with data and innovation in 1911 with punch card and other office automation machines. Since then, the data and technology that they have fostered has been used to innovate Apollo landing on the moon, launch one the first commercially available personal computers, and create Deep Blue – the first chess “machine” to win a match against a reigning human chess champion – and computers that could natural language manipulation and cognition, such as Watson, featured on the gameshow ‘Jeopardy’. These amazing advancements are great examples of evolution, and revolution in the ways in which data and automation can help us explore new frontiers and re-imagine the role of man/machine collaboration.
Today, the possibilities of data and computing continue to move forward – propelled in particular by businesses and researchers looking to adapt to future concerns, reap new benefits, and improve the human condition.
We are currently at an important point of inflection on the frontiers of what is possible with computers and automation when it comes to quantum computing, one of the latest truly revolutionary innovations in the sphere of data and computing. We are only just beginning to understand what the implications of generally available, stable quantum computers might be, an impact which will likely emerge in exciting ways in the coming years.
Quantum computing will enable computers to address new types of problems which were either computationally intractable or computationally overwhelming. The change will likely be so dramatic that this blog post will become a minor historical perspective in a short span of years. It is simply too difficult to put into words just how fast applications of new data and computing are developing. Soon problems that aren’t solvable today will be solved, new challenges will certainly emerge, and we will experience capabilities that are only science fiction today.
The speed that these solutions are emerging is why quantum is considered a transformational technology. It’s also why IBM has taken the impressive approach to democratise quantum computing, making the capabilities available to many. IBM is playing a critical role in driving a societal change that many need to shape and contribute to over the coming years.
Artificial Intelligence (AI)
The rate of increase in data availability, including volume and velocity of change, has raised questions as to how businesses are supposed to keep up with their analysis and decision-making when a mass of information is constantly flowing. It’s true that sensemaking from data can fast become an overwhelming experience. In reality, AI and other forms of automation are important components of a strategy to keep pace with the rapid change in information available to make decisions.
The pandemic is a prime example of why consuming large amounts of data and digesting it with AI and automation is essential. As the situation was so unprecedented and unpredictable, existing longitudinal data models, informed largely from an understanding of the past, couldn’t inform business’ reactions reliably in the context of a highly disrupted future. We all had to pivot our efforts into pumping out trusted data as quickly as possible so people could make decisions in real-time, based on current and near-future events. Using important capabilities in AI, including anomaly detection and natural language synthesis, data scientists were able to help the world understand what was happening in near real-time.
Ultimately, AI is an essential component of business decision-making. Yet, that’s not to say humans are a redundant part of data and computing – people will always have a place. Humans are vital in providing the thinking and decision-making prompted by the findings of data. Humans have certain advantages that will likely become ever-more important, such as intuition, empathy, artistic sense, and imagination.
The permanent reliance on human input and action within data and computing means that it’s critical to prepare the workforce with the skills they need to work with evolving AI and automation practices. The skills that have made anyone successful to date are simply not sufficient. People will have to get more familiar with technical skills, but also softer skills such as critical thinking, synthesis of information, and questioning bias and veracity.
Regulation and Innovation
Innovation will always outpace regulation. Nevertheless, it is only the combination of the two that are harbingers of business success. It is imperative for innovators to work with regulators, especially in light of the types of complex evolution that involves the intersection of data and technology.
Sci-fi movies with apocalyptic endings in particular have highlighted the frightening extremities of a data-centric world pushed too far in the wrong directions, which has created greater public awareness to the potential misuse of data and technology. These dystopian views have also encouraged greater scrutiny of data and computing innovations through regulations and as a result, there’s been increased focus on authenticity, ethics, and provenance. The future contains the potential for both great opportunity and ominous risk. We must be active participants in that evolution.
It is important not to see regulation as a hindrance, but rather as a framework. Working with a keen eye to not only what can be done, but what should be done is more a challenging opportunity, which has so far spurred on many of the innovations we’re seeing today and will continue to see within the near future.
The key thing to remember when analysing the evolution of data and computing is that you simply can’t underestimate the complexity. Yet that doesn’t mean you can’t wield the change to your advantage, to continue to learn and to teach. To do this will require a humble mindset in which your business is willing to learn, and to also contribute its learnings to the wider community.
If you’d like to hear our full discussion on the evolution of data and what’s yet to come you can listen to The Power of Data podcast here.