Neil Sahota, Keynote Speaker / Business Guru / Master Inventor / Tech Coast Angel / Author, University of California, Irvine - Paul Merage School of Business
Seems like everyone these days is talking about Artificial Intelligence and how it will transform life and the world as we know it. In the United States, policymakers are considering how AI technologies can be prevented from being accessed by China through investment and trade restrictions. Economic competitiveness and national security are considered national AI policies. And in Europe, newly installed EU Commission President Ursula von der Leyen promised AI Regulation within a hundred days of her swearing in. What did she achieve on AI with her first hundred days? This panel will look at the AI landscape in the United States and around the world.
AI is fairly nascent in the education landscape. Some solution providers use AI within their applications, especially in personalized learning and other algorithms to meet students where they are in their learning. EdTech solution providers are determining whether providing AI learning solutions makes sense and how it may impact their business including processes and practices, business models, and technological developments. Let’s dive in and look at additional ways AI is being used in the classroom, how AI is beginning to impact learning science, how AI may impact the future of work, and how business are or are not changing their business practices.
Christopher Sessums, Ph.D., Director of Academic Affairs, D2L
Artificial intelligence is expected to contribute to multi-billion dollar growth in a number of industries. Growth isn’t a problem. A lack of explainability is, especially in fields like finance, energy, and medicine. How can regulators assess AI-driven processes for which no human expertise exists? The complexity of rule-based AI systems (where the AI makes decisions based on predetermined criteria) differs greatly from artificial neural networks (where the AI makes decisions based on rules it has learned which are often hidden from human view) – do these different AI applications require different regulatory approaches? Hear from panelists about how they are using AI currently and how they are preparing for a future in which US regulation of AI expands beyond self-driving cars and smart weapons systems.
Publishers are utilizing AI and Natural Language Processing (NLP) in their businesses to crate monetized products and personalized content for subscribers. Dive into best practices with a digital publisher already employing streamlined analytics and archive-mining to generate AI-driven personalization to readers. Learn how AI is boosting the bottom line.
At its most basic level business runs on data. Policymakers around the world are grappling with how to create an environment that fosters innovation whilst also protecting personal data and guarding against exploitation. From Europe’s General Data Protection Regulation (GDPR) to California’s Consumer Privacy Act (CCPA) - the alphabet soup of privacy legislation can be daunting, but with high potential fines in GDPR and CCPA for noncompliance, they also cannot be ignored. As Congress debates Federal privacy legislation, this session will break down what you need to know about the landscape of privacy legislation as it relates to the deployment of artificial intelligence technologies.
The financial industry is tapping into new sources of data to diversify product offerings and uncover the next big investment opportunities. The term alternative data describes a broad category of information other than pricing data used to inform investing decisions. It can include anything from unstructured data such as satellite imagery to social media posts, and output from IOT sensors. SIIA members need to know that alternative data also encompasses structured data, like the specialized content your company already publishes. Learn the basics behind alternative data to understand what opportunities exist for your business.
Companies need to prepare for the killer combo: people + technology. Diversity brings quality improvements that outweigh any challenges from people of different backgrounds working together. And as De’Onn Griffin, Research Director at Gartner states, “no one will escape the impact of social developments, digital business, consumer behaviors and emerging technologies." So then, how can companies enhance trust in AI, algorithmic auditability and explainability? What do companies need to think about in proactively eliminating bias in AI solutions? In this session, panelists will discuss the undeniable need for diversity within the R&D stages of software development, best practices for embracing digital transformation, and the importance of digital dexterity.
Erica Pandey, Future Reporter, AXIOS
Charlton McIlwain, Professor, Dept. of Media, Culture, and Communication, NYU
Sharlene McKinnon, Research Program Manager, Applied Research Lab, Element AI
Frida Polli, Ph.D., CEO, pymetrics
Miriam Vogel, Executive Director, EqualAI
Whether you’re a business of 5 or 5000, incorporating AI and machine learning tools into your core functions will transform how you do business. The businesses that will reap the benefits of these new technologies are those that are able to understand it, including how to leverage it for positive changes within a workforce. But does that mean that everyone needs to learn code? Or are there lateral and collaborative thinking skills that can be taught? Speaking of training, how do you prepare your current employees to optimize these tools and overcome dooms-day thinking that technology will "steal" jobs? And what skills do you need to look for in new hires? Join us for this panel, which will explore these questions and more, to help you prepare a workforce that works with AI, not against it.