Data, AI, & Machine Learning
Data & Data Culture The Real Deal About Synthetic Data
AI techniques can generate training data that retains the predictive power of real-world data.
Fernando Lucini
- Technology Ethics
Ethics
Designing Ethical Technology Requires Systems for Anticipation and Resilience
Kirsten Martin and Bidhan (Bobby) L. Parmar
Ethics
Why Building an Ethical Culture Must Start at the Top
Robert Chesnut, interviewed by Ally MacDonald
- Leading Data & Analytics
- Data Strategy
- Technology Ethics
- Leading Data & Analytics
Data & Data Culture
Empowering a Data Culture From the Inside Out
Jonathan Tudor, interviewed by Ally MacDonald
Analytics & Business Intelligence
Leading With Decision-Driven Data Analytics
Bart de Langhe and Stefano Puntoni
- Data Strategy
- Technology Ethics
- Leading Data & Analytics
- Data Strategy
IT Governance & Leadership
The Enterprise Systems That Companies Need to Create
David Waller and Paul Beswick
Analytics & Business Intelligence
Actioned Analytics Pave the Way to New Customer Value
Barbara H. Wixom and Gabriele Piccoli
Analytics & Business Intelligence
Getting Serious About Data and Data Science
Thomas C. Redman and Thomas H. Davenport
Latest Insights from MIT SMR
Diversity & Inclusion
Democratizing Data in Hollywood: Jumpcut’s Kartik Hosanagar
Sam Ransbotham and Shervin Khodabandeh
Technology Implementation
The Human Factor in AI-Based Decision-Making
Philip Meissner and Christoph Keding
IT Governance & Leadership
Building an Organizational Approach to Responsible AI
Kay Firth-Butterfield
More Insights from MIT SMR
Technology Innovation Strategy
The Innovator’s Mindset: Creating a Better Tomorrow With AI
Kay Firth-Butterfield (the World Economic Forum), Ya Xu (LinkedIn), and Charlotte Degot (BCG GAMMA) join MIT SMR senior project editor Allison Ryder for a discussion on innovating with artificial intelligence.
Kay Firth-Butterfield et al.
Ethics
Why ‘Explicit Uncertainty’ Matters for the Future of Ethical Technology
To address algorithms’ potential harm, companies must be willing to focus on users and rethink their business models.
Mark Nitzberg
Data & Data Culture
Putting Dignity at the Core of Employee Data Use
Companies that manage employee data responsibly are better able to grow trust across the company while gaining insights.
Dorothy Leidner et al.
IT Governance & Leadership
Portrait of an AI Leader: Piyush Gupta of DBS Bank
DBS Bank’s CEO exemplifies how a willingness to experiment and even fail can help advance new technologies like AI.
Thomas H. Davenport and Randy Bean
AI & Machine Learning
Real Talk: Intersectionality and AI
In artificial intelligence, race and gender too often generate a bias double whammy.
Ayanna Howard
Analytics & Business Intelligence
Online Shoppers Don’t Always Care About Faster Delivery
Retailers should analyze customers’ preferences before deciding how to optimize their delivery networks.
Pedro Amorim and Nicole DeHoratius
Technology Innovation Strategy
How In-Store Tech Will Transform Retail
In-store technology promises a better customer experience — and fuel for improved retail analytics.
Selena Zhu et al.
Innovation Strategy
The Digital Twin Opportunity
Developments in enabling technology are opening up more use cases for virtual models of real-world objects.
Pushkar P. Apte and Costas J. Spanos
Data & Data Culture
What’s Holding Your Data Program Back?
New research highlights nine key factors impeding organizations’ ability to advance their data science progress.
Thomas C. Redman
Data & Data Culture
Fast-Track Data Monetization With Strategic Data Assets
To monetize data, companies must first transform it so it can be reused and recombined to create new value.