The US’s lead in the Global AI race is not assured. What are the geopolitical and technological implications of China’s rise, Globalization and the increase in cyber-warfare? Is the world getting riskier? What does this mean for our careers, education and governance?
Artificial Intelligence (AI) is impacting nearly every facet of human life from globalization to jobs, financial services to the role of governments, the nexus with cyber risk to spying, and from China’s quest for AI supremacy to healthcare.
The race for AI supremacy is about more than establishing a competitive position in the global marketplace for innovative applications and technological prowess – it is about anticipation, adopting the right mind set, and having the right resources, a futuristic orientation, and the ability to execute. While few organizations and governments have achieved the right mix to lead in the race for AI supremacy, those that have already possess a substantial lead. Those that have not are simply falling further and further behind.
What is required to get ahead and stay ahead of the AI curve? Daniel Wagner and Keith Furst, co-authors of the new book AI Supremacy: Winning in the Era of Machine Learning will explore AI’s impact on a societal and global level and provide a vision for how AI and machine learning will likely influence the way business is done, societies function, and governments interact in the future.
The Paul H. Chook Department of Information Systems and Statistics invites you to the second Annual Symposium on Data Analytics. The Symposium will be held on Friday October 12th, 2018 at Baruch College’s Newman Verical Campus Building located at 1 Bernard Baruch Way, New York, NY 10010. You can find the full program schedule here.
Brought to you by ACAMS (Delaware), Wilmington University, and Thomson Reuters.
We are providing this event FREE and OPEN TO ALL (ACAMS member or not), but registration through this link is asked in order to give us a good headcount to prepare. Unlike prior events, this one has two unique aspects. First, it is centered around a panel discussion and moderator that are subject matter experts regarding international sanctions compliance. Second, along with unique access to networking opportunities, employers, and sponsors, there will be a full dinner buffet. This event is aimed at offering something of value to everyone of our thousands of contacts and partnering organizations:
DataVisor is heading to NYC. We are hosting an anti-money laundering (AML) meetup event designed for compliance executives to network with their peers and listen and participate in a cutting edge AML discussion from an expert panel. The panel will discuss the role of new technology such as artificial intelligence in reducing false alerts and false negatives in AML programs and strategies to get buy-in from senior management.
In our previous webinar, we discussed smarter ways to integrate Beneficial Ownership information into compliance processes to make the decision-making process easier.
But with the sheer volume of data growing exponentially and the RegTech landscape continuously changing, how do you eliminate reliance on manual processes and integrate next generation technology into internal processes in a smart way?
Don’t miss this opportunity to get advice and insights from our experienced legal, technology, corporate and FI compliance panel as they discuss:
- Current Beneficial Ownership best practices
- Limitations of traditional processes and yesterday’s choices
- Challenges practitioners face in introducing new technologies
- The role of AI in aiding compliance activities
- Buy-in from senior management to invest in automation
- Good practice examples and lessons for considering new compliance technologies
Want to learn practical approaches to apply artificial intelligence (AI) and machine learning (ML) to your anti-money laundering (AML) program? In this webinar, Catherine Lu from DataVisor and Keith Furst from Data Derivatives will delve into real applications of how AI and ML help AML programs. They will also demystify why traditional transaction monitoring system (TMS) are struggling to keep up, and the real strengths and limitations of AI and ML.