Ontology Alignment in Business and in Life

Is a large purple ball a chair? Yes or no, "it's just semantics", right? Yet semantics, collections of choices in interpreting meaning, are actually at the core of what we value. In cognitive computing as in natural intelligence, we're called upon daily to reconcile new stories and facts in terms of concepts we already know. When different ways of modeling concepts come together, we have ontology alignment issues. Learn how critical inflection points across business, artificial intelligence, psychology, and society are actually ontology alignment issues in disguise, the risks around mishandling alignment, and techniques for keeping meaning meaningful.

In this session you will:

Learn to identify where ontologies exist, whether explicitly or implicitly
Find out how ontology alignment issues cut across both emerging cognitive technologies and historical cognitive patterns
See which architectures of systems are more vulnerable to ontology rot, and find out the consequences of ontology fragmentation, ontological stagnation, and ontology misalignment
Identify opportunities for ontology refactoring and ontology alignment, and ways to execute effectively
Learn why getting ontology alignment right is a long-term existential imperative

Richard Mallah heads research at Cambridge Semantics, responsible for their semantic knowledge integration platform's modules for combining, analyzing, finding, and operationalizing unstructured data, and analyzing all information in advanced ways. With these platform capabilities, CSI enables firms in life sciences, finance, and other industries to unlock and leverage the full range of their assets for smarter, more nimble business. Richard also serves as an active advisor to both the marketing analytics startup MarketMuse and to the scientific nonprofit Future of Life Institute regarding artificial intelligence. Richard’s deep grounding in the fields of cognitive computing, semantics, text analytics, and predictive analytics includes over fifteen years of software architecture, algorithms development, product management, and CTO-level roles variously involving knowledge representation, computational linguistics, and machine learning in finance, healthcare, and other industries.