Next Generation Artificial Intelligence


Professor Russ Newman of New York University does not believe that AI will cause humanity’s extinction. Instead, it should help enhance human intelligence and productivity and our quality of life. After putting the AI revolution into historical context, Prof. Newman discussed aligning AI with human values. At our current stage, he believes the regulatory mechanisms in place are sufficient. He explained how large language models work, what allowed them to come into existence and their future impact, describing the effect on marketing and advertising, as well as what the individual user experience will be like. A democratizing, hyper-personalized experience could take place where AI agents advocate on their owner’s behalf and negotiate each transaction with their owner’s preferences in mind. Over time, he sees a great diversification of models coming into being. Historically speaking, each groundbreaking technology that changed the world has been a net gain for humanity. What makes AI different is that if applied correctly, it could make us smarter. The question is, if AI gives us exceptional advice, will we take it?

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Cross-Platform Measurement Options from an Agency Perspective

Audience measurement is changing at an unprecedented rate. Concurrently, identifiers such as cookies are fading, and traditional models and incumbent suppliers are being questioned. In reaction to all these happenings, new measurement initiatives and a new Joint Industry Committee (JIC) have risen to establish a path toward a new video measurement framework. In 2023, the Online-Offline Metrics Working Group, within the ARF Cross-Platform Measurement Council, conducted anonymous, in-depth-interviews (IDIs) with eight key decision-makers from major agency holding companies. The IDIs focused on three major issues involving the metric situation confronting the advertising industry. This report summarizes the learnings from those interviews.

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Having In-Depth Research on Consumers’ Values Yields Tremendous Benefits

  • ARF Knowledge at Hand, CMO Brief

In decades past, demographic characteristics were considered the strongest predictors of consumers’ values, attitudes and purchasing behavior. Over time, however, they have grown to become weak predictors and correlates. In this Knowledge at Hand report, Dr. Horst Stipp, EVP at the ARF, summarizes the latest and most impactful research to date on consumer values and how researching them carefully can help shape effective business strategies and impactful ad messages.

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The ARF Handbook for Using AI in Advertising Research

Significant developments in AI have occurred in the last two years, allowing it to be used in various places in the advertising industry. One area that has received little attention however is advertising research. Recognizing this, the ARF has conducted a significant number of its own research. The product of this effort is an AI handbook that offers practical advice in several key aspects of using AI for advertising research. Moreover, an interactive function allows experts to leave comments that, once verified, will be integrated into the report, making it a living, breathing document that continues to evolve as AI advances.

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A Guide to Diverse & Inclusive Terminology, Including Definitions and Best Practices

  • Cultural Effectiveness Council

How can we more effectively understand and communicate with the diverse audiences of 21st century America? The ARF Cultural Effectiveness Council has created a guide to help accomplish this. It contains the latest information about diversity and inclusive terminology—an ever-evolving subject—specific definitions and best practices. This guide helps researchers and media and marketing professionals to recognize and understand preferred terms that are used to identify members of these audiences, to show proper respect and connect with them more effectively.

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How to Use Machine Learning to Speed Up the Product Design Process

  • MSI

Aesthetic design significantly affects consumer evaluation of products. Nowhere perhaps is this truer than for the automotive category. However, in this industry, development cycles can be lengthy. As a result, mid-generation “facelifts” periodically occur to maintain appeal. However, this process can be expensive. Recent breakthroughs in machine learning may help speed up the process in an efficient and scalable manner. Not only is this option cost-effective, but it is customizable. For those who wish to infuse nature-inspired elements into an aesthetic design, deep machine learning offers many advantages.

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