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The Imperativity of Algorithms
The important named algorithms that we call upon deserve a robust ontology.
Automatic Language Translation Still Unsatisfactory
Google Translate and DeepL Translate still have trouble recognizing the second person singular and plural and the polite form, even in very simple sentences.
Teaching Data Science Research Methods to Human Resources Practitioners: Part Three
How we took advantage of students' expertise in the application domain component of data science.
AI in the Public Interest: Education and Democracy
Now is a critical time to vigorously pursue public interests in education and to avoid a slippery slide into yielding public governance to an entirely private market view of how AI should be made available to students, teachers, and educational institutions. We need to strengthen governance of public data and more strongly shape the market for AI in education.
Why Businesses Must Untether Deep Learning
Deep learning only took a few years to make the leap from another theoretical piece of future-tech to a very real tool that's already making an impact on the business world.
GPT-4’s Successes, and GPT-4’s Failures
How GPT-4 fits into the larger tapestry of the quest for artificial general intelligence.
Teaching Data Science Research Methods to Human Resources Practitioners: Part Two
"When I heard we will be learning Python, I became anxious."
Cybersecurity Mistakes to Avoid at All Costs
Preventing unauthorized access or misuse of confidential data.
Twiddler: Configurability for Me, but Not for Thee
Online platform businesses have a distinctly more abusive and sinister character than brick-and-mortar retail chains.
Enabling AI Projects In An Enterprise
Identifying the development behaviors that have the highest chance of success for artificial intelligence efforts.
Serendipity: When Research in One Area Leads to a Positive Result in Another
A problem of the extremely optimal family of circulant graphs: when research in one scientific field gives an unexpected result in another.
Teaching Data Science Research Methods to Human Resources Practitioners — Part One
The challenge was to teach data science concepts to students who have gaps in their computer science background and are experts in human resources management and practice.
Using GitHub CoPilot is Like Having a Superpower
With the advent of Large Language Models (LLMs) and tools like GitHub CoPilot, I think we’re a step closer towards a world where software can be created by anyone. In fact, my colleague Brad Myers, who has investigated end-user programming for decades, believes that CoPilot is the biggest change to programming since Google search. I think this may be understating things. We’re going to see a wave of new kinds of software programming tools based on LLMs, and they will be transformative in how developers build and evaluate computer systems.
Three to five years from now, we won’t be talking about what ChatGPT can or can’t do, but we could be talking about how ChatGPT brought us all together, and the intellectual culture of the university began to shift.
In a single-author text (such as this one), we can assume a lot about the process. In the multi-author case, all these assumptions start to break down.
The Need For Combined Data And Analytic Governance
Numbers don't mean anything if people don't understand, or trust, the computation behind them.
Shape the Future of Computing
ACM encourages its members to take a direct hand in shaping the future of the association. There are more ways than ever to get involved.
Get InvolvedCommunications of the ACM (CACM) is now a fully Open Access publication.
By opening CACM to the world, we hope to increase engagement among the broader computer science community and encourage non-members to discover the rich resources ACM has to offer.
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