Artificial Intelligence (AI) is driving many organizations' current innovation and digital transformation efforts. While AI holds tremendous potential, the pace of its adoption by businesses of all sizes has raised concerns and challenges. Chief among these considerations is how to deploy AI models sustainably, including the governance and security of data, the social and ethical implications, and the reduction of any environmental impact.
Guardrails for the Governance and Security of AI Data
Properly managing AI models requires purposeful design and agile governance. Designers must create AI processes with a clear understanding of their intended purpose and the potential impacts on individuals, communities and the environment. Agile governance of AI requires a flexible, adaptive and responsive approach to managing and overseeing projects and initiatives. By using these two methods, businesses can use AI to support their strategic goals while meeting regulatory guidelines.
Appropriate AI rollouts are especially critical in the healthcare industry, where agility and innovation, alongside privacy and security, are must-haves. Businesses like Precision Robotics, a company based in London and Hong Kong, are working hard to ensure they build AI properly.
Healthcare is particularly challenging to scale due to labor shortages and the time it takes to train and upskill medical workforces; Precision Robotics is helping bridge that gap with its agile and intelligent AI-powered surgical robots. Every step in building the advanced machine learning required to train and develop its robots must be purposeful and mindful of the patients being operated on, while still meeting global healthcare standards and ensuring the collected data remains private and secure.
Equinix, the world's digital infrastructure company, helped Precision Robotics scale its compute-intensive training workload and run its AI servers confidently, knowing its infrastructure meets critical regulatory guidelines. With its equipment in Equinix data centers worldwide, Precision Robotics can embrace faster R&D processes and collaborate with healthcare ecosystem partners. The rapidly changing healthcare industry and various regulatory concerns around data-sharing require Precision Robotics to build an agile AI governing process that fits today's needs and is flexible enough to adapt to tomorrow's requirements.
Using AI Ethically
Responsible AI also incorporates training and using conscientious and ethical models, including removing gender, race and other biases from data sets and workflows. It also means developers must build transparency and inclusiveness into the models to help avoid discrimination.
Businesses must be vigilant in ensuring inputs are not corrupted (known as "data poisoning") and data remains secure so customers and business partners can trust the organization's AI strategy and have faith that diverse community groups were used to train models. The risks are too significant not to take privacy and compliance seriously. A wrong decision based on erroneous AI outcomes could lead to the loss of millions of dollars and irreparable damage to a business's reputation.
Financial services and healthcare are highly regulated industries actively exploring AI. Organizations must also be conscious of ethical AI risks and follow local and international regulations. By understanding and adhering to local and global rules, financial service businesses can be confident that their AI data sets and supercomputers are compliant and operating from ethical starting points while providing customers with the best outcomes.
Minimizing AI's Environmental Impact
Businesses understand that sustainable AI is vital for success but involves environmental challenges. OpenAI released data showing that the necessary computing power to run AI training has been doubling, on average, every 3.4 months.[1] Deploying a responsible AI at scale requires extensive data processing infrastructure and systems, and so sustainable AI also requires efficient and low-carbon data center operations.
Sustainable data centers are one way to address concerns about AI's impact on the environment. Equinix was the first data center operator to commit to becoming climate-neutral globally by 2030, aligned to a science-based target. It runs some of the most sustainable data centers in the industry. The company is innovating efficient ways of operating its facilities and is currently striving to draw its entire power usage from clean and renewable energy sources. Improvements include using adaptive control systems, reducing power consumption, testing alternative low-carbon fuels and increasing cooling capacity through active airflow management.
Equinix was also the first data center to commit to improving its operating temperatures, reducing the power and associated carbon emissions needed for cooling while maintaining a safe operating temperature for computing equipment. Furthermore, 70% of Equinix's global data center portfolio has retrofitted its hot/cold aisle containment system.[2]
Continental, a German multinational manufacturing company specializing in parts for the automotive and transportation industries, is one business using Equinix to ensure its AI strategy is as climate-friendly as possible. As it developed Advanced Driver Assistance Systems for autonomous driving vehicles, Continental needed to process and analyze more than 150 terabytes of data worldwide to improve safety.
With data needs rapidly increasing, Continental sought a partner able to handle the data workload and aligned with Continental's goal of being carbon neutral across its entire value chain. By operating its high-performance AI supercomputers in Equinix's data centers, Continental's supercomputers are 100% covered by renewable energy purchases, meaning it reports zero market-based emissions for the data centers in its supply chain. Through working with a partner that shares its environmental values, Continental can continue building connected and autonomous vehicles to improve the world's future while deploying a more sustainable AI operation today.
As businesses race to embrace AI, they must also ensure responsible, ethical and sustainable operations. AI is rapidly helping enterprises advance at an unprecedented rate. Companies using AI technology must operate in ways that help their business while being responsible. Equinix’s Private AI turnkey solution is built on a multicloud platform bringing AI directly to your data while satisfying requirements for data privacy, performance, and predictable costs.
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