The AI Workforce: Harnessing AI to its Fullest Potential
AI workforce is not a new phenomenon. Data and analytics are fueling an artificial intelligence (AI) tech boom which machine learning and deep learning are adding new layers to business strategy and workforce development.
Data scientists know the impact of AI is indisputable, but businesses are still in the early stages of democratizing data to harness AI’s full potential on the enterprise and its workforce. The use of emerging technology was already growing at a rapid pace in the business world and the impact of the global pandemic, the COVID-19, will only accelerate this trend, particularly in sectors such as public health, medical and education.
Emerging technology will continue to transform business strategy and empowering organizations to make smarter business decisions in 2020. AI implementation continues to rise, jumping from 48% in 2018 to 72% in 2019 according to the RELX Emerging Tech Executive Report, which polled 1,000 US senior executives at companies with at least 50 employees.
But, what does this increase mean for enterprises?
Recognize the realm of AI workforce is changing
Organizations are invested in using artificial intelligence and machine learning, but many don’t have the required talent necessary to execute their strategies. The growing skill gap stems from the many employees who have mastered the day-to-day aspects of their roles, and now find themselves challenged to learn new skills as AI is more embedded in business operations.
According to IBM, as many as 120 million workers in the world’s 12 largest economies may need to be retrained or reskilled as a result of AI and intelligent automation.
AI will not replace the human workforce. Humans can’t compete against computers for speed or accuracy of analysis; however, humans have talents that computers cannot be taught including critical thinking, creativity and experience.
The ability to make informed decisions using AI technologies is also a skill reserved for humans. Therefore, despite the sophistication and hype surrounding AI, it boils down to the fact that AI is just another tool, and it’s a tool that requires training to use it effectively and appropriately. This training is key to advancing human-centric AI, or artificial intelligence systems that learn from and collaborate with humans in a meaningful way, in the workforce.
Organizations must ensure these technologies are being implemented responsibly and provide the appropriate training of the workforce and by confirming bias is not embedded in the algorithms. By adopting a human-centric AI approach, business leaders will align with changing technologies in a way that abides by ethical guidelines and provides training to all employees who use the tools.
Make training accessible to minimize biased outcomes
As technologies are increasingly deployed to assist in complex decision-making processes, guidelines that train employees to be appropriate, ethical and address AI bias are key to an educated and prepared talent pool.
Biases are inherent to humans and often impact each of our decisions.
Remembering that AI is a tool and algorithms are built on how humans input data, the output of the AI algorithms we build can mirror our human biases. Biased algorithms can lead to unfair outcomes, discrimination, and injustice, making it crucial to address these challenges early on and implement safeguards.
Recent research revealed that a popular facial recognition software platform had “much higher error rates in classifying the gender of darker-skinned women than for lighter-skinned men.” The AI isn’t biased but it does replicate the institutional biases inherent in society. In this case, the training models used to instruct the AI algorithm to identify faces were comprised mostly of white male faces. Accordingly, the algorithm performed better identifying the faces with which it had more experience. This is one example of why testing and training AI in a workforce who understands how to build fair and ethical algorithms is the backbone of implementing AI technologies within an organization.
To prevent this bias, models and algorithms need to be continually tested in a checks and balances system. By including a wide range of technologists and people with different backgrounds during development, business leaders can further help reduce the risk of biased outcomes.
Executives can make training accessible for all employees to understand AI technologies. Democratizing data for all of those involved to collaborate, use the data, and understand the outputs to make informed business decisions is paramount.
Additionally, it is important to remember that in business, AI does not make the final decisions; humans do. AI is a tool to provide humans with information to make a decision.
Training the workforce will lead to better business decisions
Businesses across industries need to make sure that their workforce is skilled to manage these new technologies. To do this, businesses need to train their workforce – both the future workforce and the workforce they currently employ.
RELX research found a vast majority of executives (93%) believe companies should invest in the future AI workforce through educational initiatives such as university partnerships. In addition, 62% report their company offers AI training to current employees, up from 46% the year prior.
AI is a tool that can continue to assist major business decisions but it’s not going to replace the human workforce. Itis people on the front lines who make the difference in developing and interpreting AI systems that are cutting-edge but also responsible and ethical. Having a workforce that is trained on how to properly implement AI, interpret AI outputs and make informed decisions based on those AI algorithms could make all the difference in a major business decision.
Continuing into 2020 and beyond, emerging technologies will present opportunities for advancement and optimization when proper implementation is supported by training and educational programs to the workforce. As data becomes democratized and more professionals are able to leverage emerging technology in responsible, ethical ways, this shift will decrease the operational costs, expand business offerings and ultimately minimize the skills gap.