My career path to date is grounded in a fundamental curiosity for how the world around us works. My undergraduate and postgraduate degrees enabled me to explore the practical applications of statistics and computer modelling, to ask the right questions and this serendipitously led to a career in data science.
Over the past decade I have cultivated this interest in applying analytical techniques, both as an analyst in the banking sector and subsequently as a principal consultant at SAS, leaders in predictive analytics and machine learning.
Through my tenure at SAS I have helped to deliver numerous data science projects for large-scale enterprises, driving innovation in the fields of AI and the corresponding fields of machine learning, deep learning and natural language understanding. I’ve been privileged to work with, and now lead, a diverse team of highly skilled multidisciplinary data scientists, and along the way publish papers and a book on the applications of machine learning. My focus is now on supporting the next generation of data scientists, both internally at SAS and wider in the academic world, to drive forward further innovation in AI applications.
I am extremely proud of the data science function we now have at SAS. We have experienced phenomenal growth over the past year, quadrupling in size, and now provide data science advisory support across all the largest UK enterprises.
The person who I have always looked to as my role model and inspired me to achieve everything I have in my career is my father. His work ethic and drive to be the best version of himself he could be is the mentality I have tried to emulate.
At the start of 2019 I was optimistic that AI would be contributing more to UK economic growth, however, with global economic growth still hovering around 3%, 2019 saw the slowest expansion in the last decade. Many factors are weighing on the global economy, but one of the most persistent challenges has been flatlining productivity.
In 2020 it is perhaps too premature to claim that AI will still ride to the rescue, but I am confident it will make a big difference. When it comes to improving productivity, the most significant development will be the operationalisation of AI in organisations. This means the innovations, new algorithms and technologies developed in R&D will finally be rolled out and integrated into the rest of the organisation.
My predictions for 2020 are that regulation will increase, but so will corporate responsibility around the use of data in AI but the biggest driver of all will be consumer demand.
AI creators will start introducing controls to ensure their creations can’t use data in an unethical manner. Greater emphasis will be placed on the training of AI systems and the process for reviewing decisions will be strengthened. On the end user side, companies will also begin holding decision makers to account for the choices they make based on AI-generated insight.
I believe data-driven AI will deliver economic benefits as productivity increases, aided by automation technology and actionable insights. AI will be crucial to narrowing the technology skills gap that exists across several key industries, notably in healthcare, where the value of initial diagnosis will allow doctors to focus on more specialist care and treatment of patients.
With prevailing ethical concerns around AI, there is a market opportunity for companies with ethical AI solutions. Specifically, these are organisations that provide well-explained, transparent solutions that deliver better customer experiences, enhance the decisions of existing staff and help to solve social problems.
Skills in data analytics and AI development will continue to be highly prized as organisations constantly seek to compete and innovate their models and algorithms. Equally, as organisations take greater responsibility for their data and AI systems, I foresee more validation and screening focused roles will emerge.
As with every technology revolution there will be an adjustment period. To mitigate for certain employment opportunities diminishing as robotic process automation solutions are rolled out, I believe it is important for reskilling and education to begin as early as possible.