Artificial intelligence, or AI, is an area of computer science that sees intelligent machines behaving and reacting as humans do.
Computers with artificial intelligence perform cognitive functions, such as learning, planning, problem-solving, and speech recognition. Whilst there is a science-fiction fuelled misconception of the world being over-run by human-like robotic beings, the reality of AI is far removed from this Hollywood-created fantasy.
Everyday examples of AI include Siri, Amazon Echo, and Google Dot – even video games, online banking fraud detection, and purchases prediction from online retailers: the landscape of the everyday is populated with instances of AI.
As the technology industry grows and develops, the use of AI within the world of business is also increasing; within the health care, retail, manufacturing and sports industries, we have already seen this. There is no doubt that technology is at the heart of many industries – but it is limited, as technology can only do what we tell it to do. Likewise, the limitation of AI is that it learns from data – therefore any inaccuracies or limitations within the data input into the machine affects the accuracy of the results.
Chief Engineer and Architect at Invenias, Lukas Neumann, with a PhD in Artificial Intelligence and a role as research assistant in Visual Geometry at Oxford University, is in a leading position to comment. "The current thinking is that AI is only good at tasks which are repetitive and don’t require any creativity – such as searching databases, driving a car, or predicting weather for the next 24 hours," he said.
"Executive search presents different circumstances, where each individual is unique and every assignment distinct. If you are hiring a larger volume of candidates for the same position, AI might be able to help you to score the right candidates. This is almost certainly not applicable to executive search."
However, as Lukas notes, there is ample opportunity for the search industry to utilise AI in the many processes undertaken by a search professional on a daily basis. "AI can help with processing large volumes of public data automatically, to facilitate the initial search process," he said. "Allowing machines to mimic the cognitive workings of the human mind, tasks such as defining a long-list of suitable candidates for a particular assignment could become a simple automated process." The only limitation is that the machines expected to complete these functions would need to have a large amount of data input into them.
There has even been the suggestion that machines with artificial intelligence could conduct first level interviews. It is an opportunity which is on the radar of network group Boyden. Utilising AI within the search process could even help to ensure a level playing field when it comes to diversity, pre-screening and creating a list of the best fit applicants by measuring verbal and non-verbal communication skills which are scientifically correlated to success predictors.
Lukas goes on to say: "the actual interviewing and selection process will, I think, mostly be human-based in the foreseeable future. The knowledge and development of personal relationships which are so integral to the role of a search professional is unlikely to ever be mimicked by a machine. AI in the search industry will almost definitely become an analytical tool rather than a decision-making one, performing daily administrative tasks which are labour intensive. This will allow search professionals to place a greater focus on developing and maintaining personal relationships which are vital to the industry."
Technology is the co-pilot, not the auto pilot, of a search firm’s day-to-day workload. Existing and emerging technologies are valuable enablers in the executive search toolkit – but their adoption into the everyday doesn’t have to be taken in a ‘big bang’ approach. The use of AI is likely to increase within the search industry – but it will remain as a complement to the search professional, improving the efficiency of business operations.
Lukas Neumann, Chief Engineer and Architect at Invenias
Lukas has a PhD in Artificial Intelligence, and currently holds a position as a research assistant at the University of Oxford. With globally acknowledged work in Text Detection and Recognition Field, Lukas has worked as the technical lead on strategic projects for a number of prestigious companies. He has over 10 years’ experience in professional software engineering, and was recently awarded the prestigious Google PhD Fellowship.