Artificial intelligence (AI) continues to reshape all aspects of everyday life. From driverless cars and supermarkets with no cashiers to factory automation and e-learning, the roll-out of machine-driven data and automated processes are redefining how the world operates, especially across the media industry.
During a lecture at Northwestern University in Qatar, Dave Senior, partner, and strategist at Toronto-based digital agency Playground Inc. explained the difference between AI and machine learning, and the role each plays in transforming experiences and professions.
Senior explained that machine learning is the “acquisition of knowledge or skill by a computer, where the knowledge is provided and fed by an expert,” while AI is where a machine can “apply knowledge and continue to optimize” using algorithms and logic to make decisions and come up with solutions, without an expert.
“The differences between AI and machine learning are fairly stark,” said Senior. “While AI cares about the success of the outcome, machine learning cares about how accurately it represents the data that has been provided. AI performs the work for you and decides what to show you, machine learning can analyze the data, but does not make decisions on how it is applied.”
As an example, Senior explained how major media corporations such as Netflix or Instagram may use AI to personalize experiences and “make recommendations that amplify certain values.” He pointed out that by using AI, these services offer suggestions and recommendations by “continuing to optimize, which helps you to break out of your bubble and creates opportunities to explore new content, or highlights other things that might be of interest based on previous activity.”
He added that machine-driven data and AI are also being used by the media corporations to make business decisions such as “deciding how and what content gets produced,” based on the popularity of similar shows or on using headlines that can achieve higher click-through rates.
Thinking about the future of this digital era, Senior noted two main areas of concern for media and communication professionals: data bias and “deepfakes.” Because data are input into the system to provide machine learning with knowledge and AI with guidance to develop algorithms, it is essential that the data are “collected in a way that eliminates bias.” With “deepfakes,” he said, computer scientists and media experts are being challenged when confronted with fake news, images, and videos that can be manipulated, adding that it is then “our responsibility to analyze and identify what is real and what is not.”
Senior concluded his talk by encouraging NU-Q students to pursue their passion and to be curious and creative “because nothing will replace human creativity.”
