Time to read: 4 min
Artificial Intelligence is perhaps the most powerful General Purpose Technology underlying many of the exciting new developments and products unveiled at CES 2021. Bridget Karlin, IBM’s CTO and VP, talks about the “new possible” of AI, and promises that “AI changes everything”. The dedicated session on “The Power of AI” was packed with insights applicable to R&D teams across healthcare, autonomous vehicles, and consumer electronics industries.
AI的变革力是我们周围的
第一次见解是我们可能会呼唤的the hidden power of AI，即使我们明确地看待我们的多个方面的多个方面的能力和生产力，即使我们没有意识到，我们也没有意识到是什么让他们成为可能。
IBM'S Bridget Karlin通过说明我们所看到的艾美的“只是冰山一角”，开启了她的言论，而Ai已经“在我们周围提供魔法”。它正在帮助公司创造自我学习和自我修复的基础设施和系统。AI在三个方面带来了最大的附加值：（1）预测;（2）自动化;和（3）优化。这些例子比比皆是：AI有助于加速临床试验，在医疗保健中开设新的边界;它彻底改变了教育和学习系统，在那里它可以帮助创建对个别学生量身定制的个性化内容，并随着学生学习而动态调整;它已经帮助供应链，以适应震惊和减轻大流行的破坏。但这只是一个开始：卡林指出，我们刚刚开始利用三个主要的AI改进驱动因素：更大更好的数据集;更复杂的软件; and better hardware with greater and cheaper computing power. Kevin Guo, CEO of Hive, agreed that what is really impressive about AI is “the massive use of AI behind the scenes” in almost every walk of life.
Businesses should start by applying AI where it already has the greatest advantage
The second key insight is the simultaneous need to focus on applying AI where it can bring the biggest advantages. This is because today “not every problem is best solved by AI, even though more and more are”, as was noted by Eric Cornelius, Chief Product Architect for Blackberry. He pointed out that AI is excellent at tasks like threat detection in cybersecurity, because of its unparalleled ability to analyze huge unstructured data sets.
The need for focus derives from the fact that while AI sometimes looks like magic, it is really hard to do well. Jeremy Kaplan, Editor-in-Chief of Digital Trends, put it in the form of a provocative question: if AI is so good, if it can already do a better job than doctors at predicting the outcome of Covid cases, why haven’t we yet solved some of the really huge problems affecting mankind? The ensuing discussion highlighted a number of crucial complications. In some cases, as Bridget Karlin noted, applying AI is hard. This can be because the available data sets are of poor quality, sometimes embodying human biases and prejudices that risk getting incorporated into AI. Sometimes the stakes are so high that we need to proceed with great caution, as in the case of autonomous vehicles, noted Kevin Guo. And sometimes it’s because humans use AI to make the problems worse: for example, Eric Cornelius pointed out how AI has helped make phishing emails much more sophisticated, to the point where they can fool security experts.
AI will augment humans and create better jobs
第三个关键洞察力是AI可以帮助我们创造更多更好的工作而不是更换工作的方式。凯文郭强调，AI将允许我们逐步消除重复的任务 - 包括驾驶 - 并侧重于更具创造性的任务。Eric Cornelius补充说，这完全是因为AI Excels快速执行了大规模的分析，它将赋予人们更有效地使用数据，并且（1）利用人类可以通过他们的智力获得的见解;（2）利用其中一些见解来构建更好的产品和基础设施（“AI永远不会建造桥梁”）。
Bridget Carlin stressed that “every business needs to become a smarter business, and AI is the fuel that makes it possible”. IBM’s philosophy centers on three principles: (1) AI technologies should augment and extend human capabilities; (2) the data and insights belong to the individuals who generate them; and (3) AI must be transparent (“you have to break open the black box of AI”).
Key takeaways
Bottom line: AI is already empowering massive increases in efficiency, operating behind the scenes in multiple sectors of our economy; but this is only the beginning, the tip of the iceberg of what is possible. To exploit the full potential of AI though, will take hard work, bigger and better quality data sets, and first and foremost, a strong and focused effort on the part of all companies to leverage AI where it can deliver the biggest benefits, by applying it to the right problems today, while the range of problems AI can address keeps widening in the years and decades ahead.
