Despite a big outrage caused by Sophia the robot among Artificial Intelligence researchers who called it a PR trick, the general audience started to question the creative power of deep technology. Thought leaders compare a pessimistic tone of voice on the fast pace of deep technology with controversy caused by the Industrial Revolution of the 18th century. Dramatic changes are expected in the job market around the globe with up to 800 million jobs replaced by robotic automation by 2030. There is a clash of opinions on how deep technology will affect us, the global market participants, and what our future of work will look like.
Will deep technology bring us empowerment and sustainable professional and personal development or will it induce changes that we will not be able to recover from?
Let’s take a look at the relationship between human development and life-changing innovations. Driven to make labour work less heavy and boost productivity, people have always leveraged tools available to automate routine work. Fears of mass unemployment have been in the air with every progress made towards efficiency. Thus, pessimistic predictions on the future of work and deep technology are repeating the same cycle that revolves around major industrial shift. In a similar vein, experts acknowledge that the core idea behind digitalization of work is to automate mundane work and give more freedom to employees for meaningful activities. Indeed, according to the estimates of KPMG LLP’s report 2017 on digital labour, by 2025 more than 100 million workers will be affected by digital transformation.
It has been thought that machines can’t replicate analogical reasoning and perform judgement-intensive tasks. However, when machine learning, artificial intelligence and natural language processing are applied to robotic automation, this narrative will change. As KMPG LLP’s report on digital labour argues, cognitive automation is going to result in the development of systems that can mimic human processes of perception, a collection of evidence and formation of hypotheses. No wonder that we ask a question about the future of work. How do we envision it? What skills and capabilities will be in need?
Future of work: Decreasing demand for human talent? The whole model of the modern working culture undergoes radical change resulting in retraining of employees for the future of work. It is predicted that around 47% of jobs in the United States alone are at risk of replacement. Technology has taken over tasks that require muscle power and are physically demanding. Now technological development moves towards enabling robots to perform cognitive tasks as judgement-intensive work by using evidence-based learning. Deloitte Insights on the future of work name cognitive technologies as the most disruptive. Analysis of words and images will be enabled by natural language processing (NLP) which is designed to decode, interpret and predict words. Machine learning models can draw conclusions and base their strategy predictions on labelled data which can be used in personalized marketing. Identification of images is enabled through deep learning. Judgement-heavy tasks, interpretation and formulation of hypotheses are no longer activities employed solely by humans. While technology was performing tasks that require muscle power, we thought that human qualities that make us human are our competitive advantage. With the emergence of cognitive technologies which will become the pillars of the future of work and Workforce 2.0, the traditional model of work becomes fluid and it will require upskilling and ongoing development from all of us.
However, industry professionals agree that global market participants should not feel threatened and suggest a productive collaboration of machines and humans. Thought leaders predict the future of meaningful work, thus, it should not be feared but rather anticipated. As stated in KPMG’s Clarity on Digital Labor, when all the repetitive work is taken over by machines, employees have more time and space for strategic initiatives, thus, a pace of innovation across an organization will be accelerated. Experts conclude that the further development of cognitive systems will only lead to enhancement of employees’ expertise by giving them more time to innovate and freeing them from manual tasks. For example, employees can delegate mundane work to the system which employs linguistic understanding to extract information from large quantities of contracts and invoices. Time for creative and innovative work at the companies has been scarce and operational processes have been prioritised within firms. As statistical machine learning can take over analysis of a vast amount of numbers and deduct conclusions, employees will have more resources for professional growth and dedicate their attention to value-creation.
Fluid model of work, fluid concept of leadership and organization An ongoing process of organizational improvement through digital transformation puts soft skills and personality traits in the forefront of the future of work. Future of work entails blurred boundaries of leadership which require possessing more than operational expertise. Focus on relationship management and empathic communication becomes prominent in the digital economy as conventional organizational structures are disrupted and smaller decentralized teams are the new norm. As routine tasks such as leveraging large spreadsheets and analysis of the information from several databases will be taken over by machines, employees will have more time and space for strategic initiatives and higher value-adding activities.
The reality of future of work is that it is even complex to determine who is going to do the work. The rise of gig economy has already led to the emergence of an independent worker and contract-based work. Talent pools will change and permanent team composition is turning into shorter (and efficient) employer-contractor type of arrangement. Ability to adjust to several scenarios and understanding the shifting models of talent management is required from leaders of tomorrow. Namely, it requires a specific skill to assimilate a gig worker into an organization and a team, design the required steps of onboarding and simply maintain productive communication even if it has a short-term orientation. Creation of an inclusive culture is a prerequisite for upgrading your management competence and it is not easy to obtain according to a study by Deloitte. Only 16 % of employers recognize that they have capabilities for management of diverse types of workers.
The good news is that flexibility of working hours, location and time are going to become predominant. Gallup study on Gig economy and Alternative work arrangements reports 36% of U.S. workers are part of the gig economy which is 57 million people. Mckinsey Global Institute research on independent work attempted to measure freelance workforce across the US and EU and came up with162 million independent workers. By 2023 the amount of independent workers in the US is projected to increase to 50% of people. This is half of all the workforce and one of the reasons why freelancing is referred to as Workforce 2.0 or the future of work. For freelance workers, alternative work arrangements mean flexibility, multi-faceted projects and enjoyable work experience. High level of autonomy and absence of barriers such as age or limit on earnings facilitate a transfer of the traditional 9 to 5 employees to the world of independent work. McKinsey Global Institute concludes that from the market standpoint, freelance work contributes to the economy by increasing the number of people employed and the number of hours worked in the economy. Furthermore, increased engagement of freelance workers makes them sharpen skills in their respective fields of specialization. The flexibility of location is one of the metrics of the future of work which can be seen with an increasing demand for coworking spaces. With an expected number of 3.8 million members by 2020, the concept of coworking spaces entails flexibility and a hub of multidisciplinary knowledge.
Practical insights and conclusion Fast development and interference of AI into our personal and professional lives create paradoxical predictions on what is waiting for us. Numbers of vulnerable jobs that are replaced by automation remind us about the pace of technological progress and to keep a hand on the pulse. It reminds us to keep learning new skills and to sharpen our knowledge in order to be competitive in the labour market. The paradox here is that in all the discussions on automation, AI and deep technology, a concept of humanity, empathy, sensemaking and sense of giving are moving into the spotlight. Creativity, the power of imagination and complexity of the human brain is something that can’t be replicated by machines. Thus, occupations, where personal qualities prevail over operational fluency, are less vulnerable to automation. This line of thought was a silver lining of the World Economic Forum 2018 in Davos. Kai-Fu Lee, CEO of Innovation Ventures and ex-head of Google China, shared his perspective on how AI is shaping the landscape of work. He emphasized that machines are capable of a variety of tasks and can augment some human behaviours. However, machines are not capable to create human-to-human connection and not driven by creativity either. What is a set of skills that can’t be replicated by AI? According to Kai-Fu Lee, occupations that contain complexity (strategy consulting), empathy (coaches, teachers, doctors) and creativity (artists) are not going to disappear in the near future.