Trusted AI, quantum computing take center stage in 2019
“Broad AI will be characterized by the ability to learn and reason more broadly across tasks, to integrate information from multiple modalities and domains, all while being more explainable, secure, fair, auditable and scalable,” Gil wrote in the post.
SEE: IT leader’s guide to the future of artificial intelligence (Tech Pro Research)
Here are three trends that IBM researchers are looking out for in the new year that will advance the industry, according to Gil:
1. Causality will increasingly replace correlations
Most of today’s AI methods are fundamentally based on correlations, and lack a deep understanding of causality, Gil wrote.
“Emerging causal inference methods allow us to infer causal structures from data, to efficiently select interventions to test putative causal relationships, and to make better decisions by leveraging knowledge of causal structure,” he added.
In 2019, these causal modeling techniques will become more central players in AI research, according to Gil.
Many organizations that experienced data breaches and faced privacy concerns this year responded by creating ethics advisory boards. More companies are also investing in the “pillars of trust,” also known as algorithmic fairness, explainability, robustness, and transparency, when it comes to using AI, Gil wrote.
“In 2019, we’ll begin to see these efforts become central to how companies build, train and deploy AI technologies,” Gil wrote. “We expect to see special focus on transferring research advances in this space into real products and platforms, along with an emphasis on encouraging diversity and inclusion on technical teams, to ensure that many voices and perspectives guide technological progress.”
3. Quantum could give AI an assist
Quantum computing experimentation and research will ramp up in 2019, along with new research on how quantum can potentially play a role in training and running AI models, according to Gil.
“A core element of quantum algorithms is the exploitation of exponentially large quantum state spaces through controllable entanglement and interference,” Gil wrote. “As the complexity of AI problems grows, quantum computing—which thousands of organizations are already accessing via IBM’s cloud quantum computing services—could potentially change how we approach AI computational tasks.”