We propose to develop and validate a model that uses automatically extracted, high-dimensional sentence embeddings to predict the likeability and memorability of new and existing slogans.…Read More
The goal of our paper is to study whether machine learning can be used to infer tips that can help workers learn to make better decisions. …Read More
Seven pitfalls that companies need to steer clear of to effectively leverage this novel technology, and a framework to help gauge readiness for adoption.…Read More
Through Mack Institute’s Collaborative Innovation Program, Army officer Bethany Dumas WG’21 gained “eye-opening” insights into private sector innovation.…Read More
This proposal for research funding aims to develop a general tool using cutting edge machine learning methods to value patents.…Read More
Book adaptation is an important innovation source for movie production. Similar to other evolutionary product innovations (e.g., smartphones vs. dumbphones), adapting a book into a movie provides an opportunity to reach a larger audience.…Read More
In recent years, firms have started to incorporate new techniques from artificial intelligence into their decision making processes. However, these techniques come with a novel set of reputational and legal risks relating to algorithmic bias and digital discrimination. …Read More
Engineering graduate student Rahul Sharma explains why the Mack Institute’s Collaborative Innovation Program was a “critical step” in his studies at Penn.…Read More
I exploit unsupervised machine learning and natural language processing techniques to elicit the risk factors that firms themselves identify in their annual reports. I quantify the firms’ exposure to each identified risk, design an econometric test to classify them as either systematic or idiosyncratic, and construct factor mimicking portfolios that proxy for each undiversifiable source of risk.…Read More
John Roese, CTO of Dell EMC, explains that advances in AI will depend on earning human users’ trust in machine learning.…Read More
Wharton professor Kartik Hosanagar, author of “A Human’s Guide to Machine Intelligence,” walks through the evolution of artificial intelligence and points to the developments that lie ahead.…Read More
One of the most important trends in business in recent years has been the growth of Big Data and predictive analytics. The trend started with traditional analytics and the emergence of decision support systems. With advances in machine learning (ML), systems can now take in large amounts of data, learn how human decision-makers have made decisions in the past, and make decisions autonomously (achieving human-level or superhuman performance in many activities). …Read More
Wharton doctoral candidate Alejandro Lopez-Lira used machine learning to analyze companies’ annual reports and assess the top four systematic risks that affect most firms. …Read More
Marco Zappacosta, co-founder and CEO of Thumbtack, explains his solution to the fragmentation of the gig economy, effectively linking customers with suitable service providers.…Read More
Danny Lange, VP of Artificial Intelligence and Machine Learning at Unity Technologies, discusses how new technologies combined with gaming have kicked the pace of machine learning into high gear.…Read More
Artificial intelligence expert Angela Zutavern explores machine learning’s potential to enhance innovation efforts by complementing our uniquely human powers of creativity.…Read More
A well-known maxim in management is that “your people are your greatest asset”. Recruitment strategies in particular have been linked to firms’ innovative capacity, emphasizing the importance of maintaining competitive advantages in HR as a key goal of effective innovation management. …Read More
We describe the effect of social media advertising content on customer engagement using data from Facebook. We content-code 106,316 Facebook messages across 782 companies, using a combination of Amazon Mechanical Turk and Natural Language Processing algorithms.…Read More
Can machine learning techniques be used to predict high-impact, general technologies? We find that an ensemble of deep learning models that analyze both the text of patents as well as their bibliometric information can ex-ante identify such patents, accurately identifying 80 of the top 100 high generality patents in the hold-out sample. …Read More
Justin Reilly (W’10), head of customer experience innovation for Verizon Fios, projects that 80% of value creation in artificial intelligence (AI) will be in business-to-business [B2B] applications, and the rest in consumer services.…Read More
