Every company is now a technology company. No matter what business a company does, its competitive success depends in large part on an array of smart technologies, the cloud and innovative mobile applications that keep customers and employees connected and power businesses. At the same time, a thoroughly humane approach to technological innovation that is often diametrically opposed to existing approaches has now exploded and has brought companies to a new pivotal moment — a new moment of trust.
By making a decisive shift towards human-centred technology that inspires trust, leading organizations are leapfrogging their competitors and disrupting the nature of innovation that has been practiced over the past decade.
For example, machine “teaching”, first developed by Microsoft, enables non-technical people and employees at all levels of organizations to directly impose their knowledge and expertise on artificial intelligence and other intelligent systems, rather than at their mercy. Moderna and Pfizer/BioNTech miraculously develop a Covid-19 vaccine in months, not years, enabled by an AI-driven drug discovery platform that puts scientists in the driver’s seat, not brute force machine computing .
Algorithms have long been used to uncover correlations, but now they are approaching more human-like capabilities, such as common sense and understanding of cause and effect. GNS Healthcare uses its causal AI platform to not only predict which patients with metastatic colorectal cancer will respond to which treatments, but also why. Even now-familiar chatbots, like Amazon’s Alexa, are gaining the ability to decipher queries they’ve never encountered before, moving toward fully conversational AI.
“Emotional AI” designed to read drivers’ emotions may help prevent accidents caused by distracted driving, drowsiness and road rage. Early work on children with autism to help them understand and express their emotions, such a system is being created by Boston startup Affectiva, founded in 2009 by researchers at MIT’s prestigious Media Lab ( And in mid-2021 it was acquired by the Swedish company Smart) Eye). Affectiva’s algorithms read people’s faces to detect their emotions and other cognitive states.
This is an extremely complex challenge. Cognitive states such as lethargy appear gradually; facial manifestations of emotion may vary by age, gender, ethnicity, and culture. Once perfected, such systems can help drivers stay calm, attentive and awake by automatically providing appropriate interventions, alerts or suggested actions. Fundamentally, human versions of machine intelligence, such as affective AI, are more likely to convince humans that systems are improving their capabilities rather than replacing them.
Pymetrics, a Manhattan-based AI startup, is using AI to help remove the biases that undermine trust in automated recruiting systems. Pymetrics combines neuroscience-based tests and machine learning to develop a series of online tests that match job candidates with suitable job openings. As described in Quartz, companies that partner with Pymetrics ask their current employees to conduct assessments that measure attributes such as memory, attention span, altruism, skepticism, and risk appetite. Pymetrics then finds patterns of top performers across various roles. For example, a salesperson may be more inclined towards high risk/high reward, while a software developer may be more process and detail oriented. All this information is fed into the Pymetrics algorithm to evaluate candidates who take the same test when applying for different positions within the company.
There is no right or wrong answer. If the results show that candidates are not necessarily born planners, then the conclusion is not that they are “messy.” Instead, they are “improvised”. The goal is not to rank candidates, but to identify the cognitive and behavioral characteristics of job applicants that make them a good fit for a variety of positions. The test is available in 20 languages with different versions for people with dyslexia, ADHD and color blindness. Companies such as Nielsen, LinkedIn, Kraft Heinz, Mastercard, McDonald’s and Accenture already use Pymetrics as part of their job application process.
Explainable AI is an emerging system capable of explaining the rationale for its decisions, describing the strengths and weaknesses of its decision-making process, and conveying an understanding of how it will behave in the future.
With the advent of virtual worlds (3D virtual world networks), trust will become increasingly important. If we move from text, images, and video (much of which are published, shared and retained on the platform) to real-time human interaction in the form of gestures and speech, we have an opportunity to build a human, fair metaworld, transparent , privacy and security.
The imminent arrival of this more radical human technology is a vivid illustration of the true role of trust. For your company, this may be your declared value, but for stakeholders, it’s an experience rooted in trust. Achieving this requires a smart and quick grasp of the innovative new approaches that are just beginning to emerge, and leaders who, no matter what industry they are in, see opportunity in a new, fully human connection between people and technology.
In this moment of truth and trust in people and technology, the stakes couldn’t be higher. The chances couldn’t be greater. Fundamentally, human technology has brought us to a new inflection point where we can create almost anything we can dream of. As these new terms of our relationship with technology unfold, we’ll find ourselves thinking more and more deeply about what makes us truly human. Ultimately, this may hold the most fundamental hope for the future of humanity.