Career Prospects In AI: Future Trends

The impact of embedding more AI into technology will have flow on effects to non-IT roles as well; any position impacted by algorithm-based decisions, such as human resources or marketing managers, will need to ensure decisions made are accurate and appropriately delivered to the targets of the decision

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Fears around automation and the replacement of human jobs by machines have been voiced for decades. However, let’s turn the question of AI and employment around. Rather than asking what will machines be doing now and, in the future and whether they will take over work currently done by humans, let’s consider what humans will be doing, and specifically which jobs will be needed to support an increasingly AI-enabled world?

In the 1980s and 90s concerns existed that expert systems would replace human experts. Many AI start-ups popped up to deliver the vision, but when promises weren’t realised, the bubble burst with consequent job losses. The current hype around deep learning presents a similar situation with many organisations across all sectors exploring AI technology to assist with decisions as wide-ranging as cancer diagnosis, intrusion detection, recruitment, logistics, network configuration, to purchasing and sales support. 

If we perform an online search of a key Australian employment service, we note jobs with the term Artificial Intelligence are restricted to sectors of Education and Training; Science and Technology and ICT in general. Language technology, natural language processing or image processing receive almost no hits; which seems contrary to the increasing deployment of chatbots, both embodied and text only, requiring expertise in agent technology and natural language processing to provide more natural interfaces to answer the questions of customers in a timely fashion and to allow human support staff to focus on more difficult and unusual cases. 

Data science or data analytics on the other hand, return at least double figures in all sectors with Accounting, Banking and Financial Services; Consulting and Strategy; and Health and Medical, with greater than 250 current positions and significantly more hits in the Government and Defence sector. Marketing and Communications tops the list with nearly 700 positions. Robotics also gets hits in nearly all sectors with Engineering, Trade and Services, Healthcare and Medical with over 100 positions followed by Manufacturing, with Transport and Logistics around half that number.

Our search confirms what we are being told by our school’s Industry Advisory Board. Specifically, industry informs us there exists a lack of graduates with machine learning skills from computer science and the statistical data analysis skills, necessary to allow them to apply the most appropriate methods and technologies according to the task and available datasets. 

Based on advertised positions and skilled migration lists, we see strong demand for business analysts in all sectors. As the conduit between business and technical teams, it will be important for organisations seeking to harness AI technology, to ensure their business analysts have knowledge of the capabilities of current AI technology and its appropriate application in their organisation. Cybersecurity professionals will also need upskilling concerning the utilisation of AI, for example to detect and prevent breaches and prevent the misuse of AI for hacking into systems and other such harms. The impact of embedding more AI into technology will have flow on effects to non-IT roles as well. Any position impacted by algorithm-based decisions, such as human resources or marketing managers, will need to ensure decisions made are accurate and appropriately delivered to the targets of the decision, such as job applicants and customers. 

It is clear that we will need AI-educators at all levels of education beginning with kindergarten, who can expose children to computational thinking and robotics, through to academics at the tertiary level to deliver graduates of AI programs. AI Educators will not be confined to IT Departments and Computer Science Schools, as we already find courses related to AI are and will be designed and delivered across most, if not all faculties. Similarly, in industry including commercial, not-for-profit and government organisations, there will be a need for AI-savvy policy makers and managers able to identify how best to harness AI technology. These staff may need to gain additional formal qualifications or certifications or undertake on the job training programs delivered by industry trainers.

A common phenomenon of AI-technology is that once technology matures, it becomes invisible when embedded into other technologies; this has been true in the case of databases, web services, recommender systems and search engines and in products and devices such as phones, car navigation systems, washing machines and vacuum robots. AI also drives less mundane applications such as drones and driverless cars and any applications requiring multi-modal sensors and actuators or knowledge representation and reasoning. Non-player characters (NPCs) used in serious games for simulations and training, or games for leisure are also driven by AI-technology, hence they are often called AIs. AI technology will play important roles in realising the visions of emerging technology areas such as the internet of things, which will support smart homes and cities and augmented, virtual and mixed reality essential for realising the metaverse dream. Current demand for jobs involving the internet of things are found within most sectors, with greatest demand stemming from the Call Centre and Customer Service, Government and Defence, Education and Training and the Trade and Services sectors. However, there is only niche demand for virtual and augmented reality at this stage.

Humans are complex and capable of many different behaviours ranging from image, sound and text recognition; planning, reasoning and decision-making under uncertainty; verbal and non-verbal communication, locomotion and manipulation of objects, to emotion expression, recognition and empathy. What is clear is that to create AI technology replicating the behaviour of intelligent life, we not only need IT specialists trained in image, text and natural language processing, machine learning, knowledge representation and reasoning and robotics; these specialists also need to work hand in hand with experts from other disciplines such as psychology, philosophy, law, education and business to ensure algorithms and interface designs perform correctly and are fit for purpose for their intended contexts and users. As well as discipline experts, specialists from application domains such as health, education, transportation, logistics and construction, will work with AI technology, governance, policy and human factors specialists, to solve organisational as well as societal problems including global warming and food shortages.

Whatever the future holds in terms of careers in AI, IT professionals and other stakeholders will need to be trained to understand the ethical implications of their designs and implementations, possibly with dedicated roles, to ensure ethical responsibility. As technology in general and artificial intelligence in particular advances, it is essential individuals and society in general continuously review and adopt correct uses of technology in our lives. From an ethical perspective, in line with the AI4People framework, we need to ask ourselves what good is delivered (beneficence), what are the potentials risks of harm (non-maleficence), is human agency respected including consent (autonomy), is the outcome unbiased and fair and equitable (justice), and does it adhere to principles of accountability, responsibility and transparency (explicability). 

Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house

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