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19 June 2023
Dan O’Connell, chief Ai officer, Dialpad
Data science in the age of artificial intelligence (Ai) has become a somewhat chaotic and unpredictable territory. With Ai rising in prominence, the role of data scientists will be greatly changed – in a few short years, the role may look completely different.
Since the release of OpenAI’s ChatGPT in 2022, concerns about Ai replacing jobs have grown in prominence. Globally, almost 95% of employers looking for tech talent have found a tech skills shortage over the past year. While tech jobs including coders, computer programmers and software engineers are still in high demand, it is possible for Ai tools to help fill the skills gap in the near future. Data scientists are also included in the list of jobs that are ‘amenable’ to Ai technologies replacing some of their work, because Ai is skilled at crunching numbers with a high degree of accuracy. This does not mean the role of data scientist will cease to exist, just that it will look quite different in the future.
As a result, data scientists need to truly understand their evolving responsibilities and ensure that they are constantly acquiring new skills in order to remain competitive in an Ai-dominated landscape.
The impact of generative Ai on data science
From ChatGPT, to Google’s Bard, to Microsoft’s Bing AI, generative Ai is moving at a rapid pace. With ChatGPT gaining over 100 million users in January, the Ai arms race has been heating up between some of the world’s biggest companies with no sign of slowing down. It is no shock to hear that the increased development of generative Ai will impact what the future holds for those that work in the data science field. However, this is not necessarily a bad thing – the skills that data scientists already have will be crucial for shaping the workplace of the future and determining what this technology will look like.
The sheer volume of data generated by Ai models can be overwhelming, requiring new skills and technologies from data scientists to manage and analyse effectively. Traditionally, the role of data scientists is to analyse data for a company to create business strategies and empower decision making. Ai can analyse data at a much faster rate than humans, which may create a fear of being replaced by Ai at work – also known as ‘Ai anxiety.’
However, we cannot shy away from the inevitable. The world is changing significantly because of the rapid development of Ai, and data scientists should embrace the opportunity and see it as a blessing rather than a curse. Generative Ai has the potential to greatly enhance the speed and accuracy of data analysis, allowing companies to make better and more informed decisions. In reality, Ai has the ability to assist data scientists in their work, by automating repetitive manual processes and allowing room for data scientists to engage in more complicated, innovative projects.
New skills for data scientists to remain competitive
New skills are always needed when it comes to work, but for data scientists, it is becoming more important than ever to develop the skills that separate them from Ai. One key area of focus for data scientists will be the ability to fine tune these large-language models (LLMs) and train the models for maximum efficiency and accuracy. In addition, Microsoft’s 2023 Work Trend Index Report revealed that the top skills that leaders believe are essential in the age of Ai are analytical judgement, flexibility, and emotional intelligence. This further demonstrates that the role of human data scientists will continue to be important, they will simply need to adjust their skill sets to work better alongside Ai.
The ability to communicate effectively and tell stories with data is also a key skill - understanding how to analyse and interpret the data and explain it in a way that is engaging and understandable for non-experts. Then, being able to take that raw data and transform it into actionable business objectives. These are all things that cannot be replaced by Ai, and there’s an opportunity for data scientists to lean on these ‘human skills.’
The role of human oversight in Ai
The role of human oversight in the use of Ai and generative models should be critical for data scientists. While these technologies can greatly enhance the speed and accuracy of data analysis, they also pose significant risks if not properly managed. Data scientists must play the essential role of ensuring that Ai is used responsibly and ethically. This includes developing protocols for data privacy, transparency, and security.
Ai needs continual parenting, particularly for chatbots. This means ensuring that the correct amount of human oversight is involved as chatbots generate outputs. It is crucial for data scientists to ensure that Ai is parented so that false or inaccurate information is not shared with the public. Despite the potential for Ai to automate many tasks, there will always be a need for human expertise and oversight.
Generative Ai is changing the landscape of data science, bringing with it a range of new opportunities and challenges for those working in the field. While generative Ai has the potential to revolutionise the world of data analysis, it is also an opportunity for data scientists to gain new skills and be at the forefront of the Ai revolution.
