July/August 2017, [Volume 26, Issue 7]
Features
Innovation: managing ideas at scale
Judith Lamont, Ph.D. //
03 Jul 2017
Innovation is a hot topic these days, with disruptive business models and new products challenging established leaders. It covers a wide range of diverse concepts and processes....
The smart thing to do: practical applications of monetizing big data in finance
Jelani Harper //
03 Jul 2017
In financial services, the dangers associated with monetizing big data are nearly as great as the rewards. The promises of machine learning, data science and Hadoop are tempered by the realities of regulatory penalties, operational efficiency and profit margins that must quickly justify any such expenditure.
Text analytics: not just for customer sentiment
Judith Lamont, Ph.D. //
03 Jul 2017
Sentiment analysis is one of the most prevalent uses of text analytics, but the technology has many other valuable uses. Text analytics finds a range of applications in scientific, medical and technology development.
Knowledge management in financial services: Collecting and sharing information and analyzing data and social media content are among the benefits.
Phil Britt //
03 Jul 2017
Financial services firms are using knowledge management solutions for data sharing across the organization, to permit authorized access to sensitive information while blocking unauthorized access and to analyze potential investments.
News Analysis
Using AI in an uncertain world
Sue Feldman //
03 Jul 2017
Human thinking balances AI systems. They can plug each other's blind spots. Humans make judgments based on their worldview. They are capable of understanding priorities, ethics, values, justice and beauty. Machines can't. But machines can crunch vast volumes of data.
COLUMNS:
David Weinberger
The future of predictability
David Weinberger //
03 Jul 2017
We believe the future is determined by a set of scientific rules operating on a set of data too vast to be perfectly comprehended.
The Future of the Future
What not to worry about
Art Murray, D.Sc. //
03 Jul 2017
There's still plenty of thinking, innovating and discovery that needs to be done. Use machines as your tools, not as your master.