Emerging Technologies

From climate to coding, AI’s impact is ramping up. These 7 principles ensure it remains human-centric

To deliver on the promises of AI and avoid the pitfalls, these seven principles can guide how organizations introduce the new tech into their work.

To deliver on the promises of AI and avoid the pitfalls, these seven principles can guide how organizations introduce the new tech into their work. Image: Getty Images/iStockphoto

George Oliver
Chairman and Chief Executive Officer, Johnson Controls
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Artificial Intelligence

This article is part of: World Economic Forum Annual Meeting
  • Artificial Intelligence is set to overhaul how companies all over the world do business, and how workers of their jobs.
  • To deliver on the promises of AI and avoid the pitfalls, these seven principles can guide how organizations introduce the new tech into their work.
  • Many workers are already upskilling themselves with AI — if companies get ahead, it can provide them a competitive advantage.

How much control do we have over the future of the planet? Quantifying humanity’s impact on global warming – and establishing measurable goals to reduce that impact – often seems like the easy part. Understanding where and how to take action can prove more challenging.

Through AI (Artificial Intelligence) and innovation, organizations are transforming the way we solve the climate crisis, radically changing the way we design, deliver and deploy the things that humans create – buildings, infrastructure, machinery, consumer products and more.

However, for organizations to truly benefit from the value of AI, we need people with the right skills to harness its value and bring it to bear against the climate crisis. And we must bring the industry along, showing the value of AI through repeatable outcomes that lower emissions and lower costs.

AI reinforces the criticality of upskilling, reskilling and training the future global workforce. Just as the pandemic changed how we work, AI is disrupting how we view the workforce.

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The promise of AI

As part of a broader ecosystem of innovation, AI delivers significant possibilities for carbon-reduction and sustainability applications. It can unlock more meaningful and business-specific insights and trend analysis. It can create — through generative applications that produce content such as designs, reports and forecasts. And it can do real work — autonomously executing business processes and controlling systems while learning and adding to its own intelligence.

All these capabilities will be essential for creating and operating more sustainable buildings and other human-made environments – for helping us take more intelligent action and to do so more efficiently and effectively. But AI alone cannot create a net zero world and solve the climate crisis.

Humans will need to combine AI with other technology to move the needle faster. We will need to integrate it with IoT (Internet of Things), digital twin, metaverse technologies and other emerging applications to create a deeper impact and accelerate action. Bringing together all these technologies requires new insights and action on multiple fronts.

But the real need in the future will be reskilling and upskilling our workforce.

From software engineers to field technicians, generative AI is becoming a core part of Johnson Controls’ operation — it’s being used in everything from developing new technology to predicting and preventing system failures or aiding those in the office to work more efficiently.

Develop use cases for today and tomorrow

With AI, the applications for sustainability and carbon-neutrality are significant. Buildings represent 40% of global greenhouse gas emissions. To achieve decarbonization goals, making our buildings smarter and more efficient should be the largest area of focus for the entire value chain, from C-suites to government leaders, to building owners and operators. It’s where they can get the most value for their investment — it’s good for the planet and the bottom line.

The question is how we get there. A majority (52%) of workers believe that working with AI will accelerate their career growth; however, only 13% of the same cohort said they’ve been offered AI training. This is a huge opportunity for employers to lean in and assess the skills that their workforce needs. Research also shows that organizations continue to see returns in the business areas in which they are using AI, and they plan to increase investment in the years ahead.

Despite these numbers, employees are increasingly educating themselves, as organizations start to contend with different rates of adoption. Moving forward, businesses will need to align capabilities with expectations for every role across companies and provide guardrails for the eager and risk-free opportunities for others. This period of learning and trial and error is crucial during this early phase of handling generative AI. Leveraging insights learned from experimentation will help build a culture of responsible usage and illuminate unseen impacts on the future of work.

7 principles for human-centric AI

Governance and ethics are imperative to the future of sustainability-focused AI applications and the use of other emerging technologies. Johnson Controls has anchored its AI ambitions in a tailored and robust code of ethics that will guide the company as it works to make the world smarter, healthier and more sustainable — and the principles are a good starting point for any organization that seeks to ensure its usage of AI is as responsible as possible.

Rather than being set in stone, these guidelines are open to evolving alongside the technology.

Empower humans in buildings: Design AI to augment and elevate human intelligence and human work.

Fairness and inclusion: Develop and use AI in a manner that minimizes the creation or reinforcement of unfair, biased and discriminatory impacts.

Privacy by design: Develop and use AI within a privacy by design framework.

Robustness, safety and security: Apply strong testing, safety and security practices to minimize unintended results or outputs from AI systems and to include appropriate human oversight capabilities.

Accountability: Be accountable for how AI systems impact the world.

Transparency: Be clear about when, why and how AI systems are deployed and help customers and partners do the same.

Sustainability: Develop AI with sustainability as a focal point to help buildings and communities become more sustainable.

Human-centricity is at the core of that AI ethics code, and sustainability is one of its key pillars. Ultimately, it helps ensure that AI-enabled solutions allow some of the largest and most complex buildings in the world to become more sustainable.

Leaders: act now on AI, or risk being left behind

The future is coming fast, with AI and other emerging solutions continuing to evolve. As the urgency of climate change accelerates, organizations will have to accelerate their adoption of game-changing technologies. The hard part of climate action is getting easier, and we can expect it to become even easier as technologies improve and as more organizations successfully adopt these technologies.

For many leaders, it may feel as if the future of the planet is out of your control. Just as the invention of the internet, smartphones and video streaming were disruptive, companies that do not innovate get left behind. Leaders must prepare for the future. Seek out training; consult with experts. In the end, the answer to harnessing AI is found within people, not machines.

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The views expressed in this article are those of the author alone and not the World Economic Forum.

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