With artificial intelligence increasingly used everywhere around us, the global AI market is forecast to reach $432.8 billion in 2022. As it becomes more prevalent, we sense a shift of emphasis to AI increasingly being viewed as a human enhancer. AI augments human performance, making it increasingly regarded as a colleague rather than a job competitor in the workplace.
Looking back, the first round of digital technology gave us email, with its benefits of ease of use and instantaneous delivery of information worldwide. However, that same ease of use, with a tendency to copy too many people and send messages out of regular hours, helped foster an “always-on” culture. Many people experience stress from email overload that reduces their efficiency rather than improves it. AI-driven smart tech offers the potential for us to automate jobs at a personal level, creating space for us to maximize human interventions.
How to plan introducing AI to your organization
As more and more organizations grasp the nettle of digitalization, either introducing AI or being left behind by their competitors is a key aspect. It’s useful to have a simple approach to address the challenge of adopting technology while remaining human-centered. One is offered in a recently published book called The Smart Non-Profit, co-authored by Alison Fine and Beth Kantar. It would seem to readily apply to commercial enterprises as much as non-profits.
- Identify pain points that further applications of more human input are unlikely to resolve.
- Select the right smart tech to employ.
- Pilot it with the use of a virtuous circle of testing with feedback loops to learn what’s working and what isn’t, and improve.
Identifying pain points ought to be part of an initial benchmarking exercise. They could exist anywhere in Operations, Marketing and Sales, Finance, and HR. Or maybe they are a less obvious side effect of an ailing company culture, which AI would be able to identify to begin the process of introducing AI.
CultureX harnesses AI developed at MIT, and can assess books and books worth of written content produced by employees. Content sources include personal reviews, employee review websites such as Glassdoor, internal surveys, and perhaps employees’ social media. Whether it includes the company’s email system can be a contentious personal privacy issue. Though with interpretation skills based on decades of evidence-led research and work with dozens of Fortune 500 companies, CultureX assesses a company’s culture with high accuracy and pinpoints concrete ways to improve it where necessary.
Cobotting
Cobotting is the use of a collaborative robot where humans and robots are working in close proximity, and the robots have a role as an assistant or guide so that AI augments human performance. They are increasingly used in Customer Service call centers. Robotic assistants can scan data for the best response to a customer need much faster than a human, and then provide the human call center agent with the solution. It’s been found to reduce agent stress, improve productivity, and reduce employee churn.
The Trevor Project, an American non-profit organization based in California and founded in 1998, provides crisis counselling to suicide-prone teenagers in the LGBTQ community. It created a chatbot named Riley to provide 24/7 training support to its volunteer counsellors, who focus on suicide prevention, by creating life-like scenarios for them to have to deal with.
At the Benefits Data Trust in Philadelphia, call center staff help callers navigate complex applications for public benefits. Public benefits like SNAP, WIC, CHIP, and Medicaid can help families in need pay for food, healthcare, housing, and more. Yet even before the pandemic, more than $60 billion in benefits went unclaimed each year in the United States. BDT staff have access to AI-driven support trained on thousands of interactions to identify and offer them the best solutions to give callers. The system can also pre-populate application forms.
AI enhancing healthcare
There appears to be a near universal shortage of trained nurses in the world’s healthcare sector. The pandemic put them under immense stress and threatened their personal welfare. Rising inflation and inadequate pay rises are contributing to a forecast of mass resignations. A February 2022 McKinsey report suggests 32% of US registered nurses (RNs) may leave their current direct-patient-care role. Fresh research by the Nuffield Trust, an independent think tank on health issues, shows the National Health Service in England is short of 12,000 hospital doctors and more than 50,000 nurses and midwives.
Nurses operate a wide range of technical equipment. Training as a nurse in the UK requires gaining a degree, a three year process. Yet some of the tasks remain menial and simplistic. A growing number of robot assistants are becoming available to take on routine tasks, leaving highly qualified nurses to concentrate on more complex matters.
In Australia, Diligent Robotics has created Moxi, a mobile manipulation robot that is doing fetch-and-deliver tasks for hospital staff. It carries lab samples between the nursing unit and the central lab, collects medications from the pharmacy, delivers lightweight equipment from central supply, or fetches a lunchbox for a staff member who cannot take a proper break. Introducing hospitals to Moxi can be the start of a process for a hospital CIO to develop a full robotic strategy, a strategy that can include robotic surgeons for AI to augment human performance.
There are differing points of view as to whether robotic assistants to nurses and doctors can interact directly and successfully with patients. A recent article in the Economic Times of India spotlighted four skills that it claimed could never be replaced by AI. It asserted empathy is unique to humans, and AI is unable to read into the situation or the face of another human because it lacks emotional intellect
However, the Hong Kong-based Hanson Robotics has created a humanoid robot it hopes will revolutionize healthcare. Designed as an assistant for doctors, the robot, named Grace, is equipped with sensors, including a thermal camera to monitor patients’ temperature and pulse, and helps doctors diagnose illnesses and deliver treatments. The android is also a companion for patients, designed to specialize in senior care. Grace can socialize and conduct talk therapy in English, Mandarin and Cantonese.
Breaking the spoken language barrier through AI
Robotic talk therapy success depends on at least sounding human. The growth of robotics for use in healthcare is happening at the same time as the development of metaverses. In just a few years’ time, we will be having 3D business meetings in a metaverse rather than 2D meetings via Zoom or some other video conferencing suite.
Fashion houses and retailers are opening metaverse stores so that our avatars can “dress to impress.” Without leaving our own spaces we’ll meet with people from anywhere around the world in 3D venues and locations via VR headsets. Communication among avatars/people who do not share the same language means breaking language barriers. Machine learning and AI have been developing instant translation services, and Zoom claimed it would have a spoken translation service up and running this year in 12 languages.
It’s certainly an appealing and lucrative challenge for speech dataset collection and AI training service providers such as Defined.ai (formerly DefinedCrowd). Their founder and CEO, Daniela Braga, is definitely interested. Daniela took part in May 2022 in a New York Times-sponsored WEF recorded debate on “The Metaverse is an ‘Opium of the People’ in the Making.”
Streamlining bureaucracy with AI
The UK, like many countries, has a housing shortage. Much of the blame is put on a non-uniform system of planning permissions across the country that leads to construction delays and project funding insecurities. The second largest city, Birmingham, is working with Urban Intelligence to speed up its approval processes, by applying AI to a database of all previous applications and matching them against available sites that could be built on. This much more speedily identifies the most relevant sites to develop, and shortlists what types of homes are most likely to fit the local conditions and requirements.
Using Urban Intelligence’s analysis software, Birmingham City Council will be able to assess nearly 330,000 sites, which is nearly 300 times more than the 1,160 sites that were assessed in 2017. It also reduces the time it takes to submit the shortlist of sites that will be retained, from eleven to three months. It’s certainly an area where AI enhances human performance.
Over to you. We’d really like to hear from you if you work closely with AI, and about how much it has transfromed your role and responsibilities.
