“It’s not enough to merely procure and combine disparate technology components”
Sarah Lyons
HEAD, PRIVACY ANALYTICS
“Safe, responsible, and trustworthy uses of sensitive information and AI/ML align with evolving global standards, regulations, and guidelines, which continue to be the central themes underpinning technology innovations worldwide.”
The following three technology trends are accelerating the evolution and adoption of Artificial Intelligence (AI) and Machine Learning (ML)-based systems:
The unprecedented pace at which ML model sizes continue to increase, for example, Microsoft’s recently announced 530B-parameter Megatron-Turing NLG model, representing a whopping 50x increase in only two years.
The continued scalability and affordability of storage and compute, including ML-specialized hardware and managed APIs available through public cloud offerings. The constant increase in the volume, variety, and velocity of structured and unstructured data is generated every day by wearables, medical devices, and IoT.
The resulting improvements to AI-based systems have paved the way for numerous revolutionary applications which were not previously possible. Personalized medicine, computer-aided diagnoses, and automated decision-making are some examples of the many exceptional innovations stemming from AI/ML.
Although such advancements create immense opportunities for business and society, they require careful consideration, such as protecting the privacy of people represented in sensitive data, and the ethical uses of AI/ML are key priorities.
The drivers & disruptors for the technology innovations
Safe, responsible, and trustworthy uses of sensitive information and AI/ML align with evolving global standards, regulations, and guidelines, which continue to be the central themes underpinning technology innovations worldwide. These themes have sparked several other technology advancements in data privacy, such as departing from traditional data masking techniques to more sophisticated methods of statistical anonymization, synthetic data generation, and probabilistic privacy-preserving data linkages. Appropriate techniques help organizations achieve more robust privacy protection, reduced bias, and higher data utility resulting in trusted innovation that benefits everyone.
Aggressive adoption of advanced technologies for staying relevant and competitive
Laggards are at significant risk of becoming irrelevant, but so are hasty or naïve technology adopters. While advanced technology adoption will undoubtedly be a part of any competitive business strategy, current problems require complete solutions supported by broad and deep human expertise.
It’s not enough to merely procure and combine disparate technology components available to the masses. Leaders in this technological race will recognize the value of blending proven technology with unmatched human knowledge to gain an edge in today’s competitive landscape.
