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Can Corporations Cure Burnout with Artificial Intelligence?
Why It Matters:
- Burnout costs corporations $322 billion annually including: healthcare costs, turnover, and loss of productivity.
- The 2022 mass layoffs are leaving the remaining staff with more to do with fewer resources.
- Artificial Intelligence advances are making burnout detection, monitoring, and prevention more accessible.
- Senior leaders should consider their response and evaluate if these AI advances could play a critical role in their firms.
From the Great Resignation to the Great Layoffs
Almost overnight, Human Resource (HR) departments went from fire-fighting resignations and accelerating recruitment to sacking staff in droves. The economic downturn has hit BigTech companies, with social media particularly exposed to the slowdown in advertising.
The recent wave of layoffs swept 134,164 jobs in 834 tech companies across the United States. What’s often overlooked are the employees whose jobs were spared.
Those who managed to keep their jobs experience mixed feelings. In some cases “survivor guilt” or anxiety about being included in the next wave of cuts. A major concern is the reckoning of delivering job at hand without the former team and fewer resources.
Studies show that nearly 74% of employees retained after layoffs saw their productivity decline, and 69% said the quality of their product deteriorated.
Before the mass layoffs, burnout was already costing the US economy $322 billion annually. The “burnout epidemic” will be augmented and prolonged when compounded with the economic downturn and new swaths of layoffs.
Can Artificial Intelligence Ease the Burden?
Artificial Intelligence (AI) has been used to rank job candidates and analyze employment sentiment among other uses. AI can now be used to look for signs of employee burnout and other mental health issues.
AI systems can understand brain functions better than ever before. Deep learning can model how convolutional layers and recurrent connections in the brain’s cerebral cortex control the memory, visual processing, and motor control. Neuro inspired AI is being used to understand how changes in the brain result in psychopathologies and how it can be utilized in treatments.
Natural Language Processing (NLP) is also being deployed to analyze sentences to identify a specific behavior. A model was constructed by collecting 13,568 samples of anonymous texts through Reddit. The method had a success rate of about 93% in identifying burnout cases.
Today these models complement but do not replace mental health professionals. The accurate interpretation of human emotions continues to be a challenge for AI. Emotion AI, or Affective Computing, refers to the branch of AI which aims to process, understand and even replicate human emotions.
While we can find affect-recognition tools at airports, recruitment, and policing programs, a 2019 systematic review of the scientific literature on inferring emotions from facial movements, led by the psychologist and neuroscientist Lisa Feldman Barrett, found there is no reliable evidence that you can accurately predict someone’s emotional state in this manner.
AI can categorize expressions and tone. It can classify emotions based on a sentence, but it is yet to “understand” feelings, cultural references, sarcasm, and nuance in language.
GPT-3 (Generative Pre-Trained Transformer 3) produces a quality of text and interactions that are difficult or impossible to distinguish from that of a written human. GPT-3 is the third-generation language prediction model in the GPT-n series created by OpenAI. Its astonishing capabilities stem from reading the entire internet, or at least a non-trivial portion of it.
Researchers made an OpenAI GPT-3 medical chatbot as an experiment. It told a mock patient to kill themselves.
As promising as GPT-3 may sound, the technology is not quite ready to replace “Dr. Phil”. It told a mock patient to kill themselves and induced somebody else to get back to work. The current training is not sufficient to process the scientific and medical expertise that would make it useful for medical documentation, diagnosis support, and treatment.
Artificial Intelligence Burnout Solutions
Automation of Repetitive Tasks
Creating weekly reports, backing up files, to-do-list management, answering common customer service queries, and completing online forms are typical repetitive tasks that AI can eliminate.
Instead of having employees complete these tasks, AI can do the job. Save an employee from answering the same customer service question multiple times in a day and your employees will be happier and more productive focusing on higher value tasks.
Spot Trends that Point to Issues
AI can track material changes in productivity or increased use of language that could be related to burnout.
The collection of data and pattern recognition can be aggregated at a system level, with or without the knowledge of employees. It can also be submitted voluntarily by employees.
HR departments can use this data for detection, monitoring and to take corrective actions.
In most cases, people are hesitant to admit they are suffering from burnout fearing negative consequences. The use of aggregated data can point to the source of issues, the types of activities that cause burnout, the time in the cycle when burnout is pronounced and it may inform the correlation between these trends and turnover, loss of productivity, absenteeism and deterioration of product or service quality.
AI Personal Coach
Introducing coaching and therapy at work can be expensive, sessions can be long and hard to schedule and some people may be hesitant to reveal their work frustrations to a coach paid by their employer.
The earliest forms of AI were created based on principles of psychology. AI chatbots or text-based apps can offer temporary relief, insights and coaching in different ways. These tools are always accessible, sessions don’t have to be long and the data can be anonymised.
Artificial General Intelligence (AGI) that is personalized to the staff (e.g., healthcare workers) helps users understand what they are going through, injecting stimuli to challenge themselves, learn and get the tools and insights to recover and feel well.
Which Solutions are Leading the Way?
Top Process Automation Companies
Robotic Process Automation (RPA) solutions are highly variable. Some deal with robotics used in automotive or manufacturing, while others optimize customer service queries, filter candidates in recruitment processes, produce weekly reports, create to-do lists, or fine-tune marketing and sales items. That said, here are some of the top companies automating processes across industries:
IBM Robotic Process Automation (RPA) automates business and IT processes at scale. It harnesses bots to act on AI insights to complete tasks without lag time and enable digital transformation.
Nice RPA’s software robots operate in back-end servers, with the capability to take over all of the repetitive, admin-driven processes. Tasks are executed independently without human intervention.
The SS&C Blue Prism intelligent automation platform combines RPA, AI, business process management (BPM), and machine learning (ML) to help organizations achieve various business goals. The company offers support from automation specialists, prebuilt automation, and training and certification. It targets large enterprise customers across different verticals via industry-specific offerings.
Power Automate by Microsoft
Power Automate by Microsoft empowers people to build automated processes with flows in Power Automate. The low-code RPA tool connects to hundreds of pre-built connectors that automate repetitive tasks. The tool is ideal for those using the Azure platform.
Workfusion takes a no-code/low-code approach using drag-and-drop building blocks, pre-built steps and workflows to make core processes integration-ready. It targets those lacking RPA development and integration expertise within North America.
Automation 360 by Automation Anywhere is a cloud-native intelligent automation platform used by enterprises to automate processes with minimal infrastructure. It released the Automation Success Platform which is said to accelerate business transformation by making automation more accessible.
Burnout Detection Solutions
Erudit AI Inc is a SaaS AI tool that analyzes video and text communications on Zoom, Slack, and Microsoft Teams. The tool identifies words that may suggest a problem. A quantitative analysis compares what the employee is saying and the distributions of other mental states that the algorithm is trained to recognize.
Uplevel is designed to monitor engineering effectiveness. The AI tool analyzes code repositories, interrupted working, calendar entries, and messages. The working assumption is that interrupted working leads to compensation for lost time at night which leads to burnout.
Uplevel data is shared with engineers so they can see the data it collects from them. It pinpoints where the bottlenecks are happening so they can be fixed.
R3 Continuum has created an emotional support bot that links to a help desk. It has an algorithm to measure the current stress levels of each state relative to each other.
Kona integrates with Slack to setting daily mental health check-ins to gain insights and spot trends.
Personal Artificial Intelligence Coaches
Woebot Health is an AI-enabled chatbot that uses Cognitive Behaviour Therapy (CBT) to deliver a mental health app for employees. The app incorporates a library of products and solutions tailored to specific mental health needs.
BIPOC-designed Ladder is an AI mental health app that tracks your moods and helps you build healthy habits.
Breathhh is an AI-powered Chrome extension that automatically delivers mental health exercises when you need them based on your web activity and behaviors online.
Misu is a Mac application that automates mood tracking by reading your facial micro-expressions throughout the day and generates infographics to help you visualize your moods over time.
Business leaders can prepare to take preventative action by implementing artificial intelligence to increase productivity, and efficiency and to maintain engaged and motivated teams.
Automation, burnout detection, and self-help AI tools are already delivering tangible benefits to businesses’ bottom lines while improving the well-being of employees. It can also make companies more attractive to new hires and retain people longer.
Robots or AI in apps provide a judgment-free zone that can be appealing because of the stigma burnout still has in society.
While the advances in AI, particularly GPT-n, are promising, a comprehensive solution to burnout still needs a combination of humans and machines. The insights provided by AI can support better decision-making but not replace it, at least not in the near-term future.
About the Author
Ela Hunter is an experienced operator and investor with more than 15 years of executing transformative growth programs across various technologies, financial services, and renewable energy.
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