Since the online profile of the publishing business tends to sink around the holidays, PG tends to go a bit farther afield for TPV during this time. That said, Artificial Intelligence is, at least for PG, a fascinating topic.
The business world’s enthusiasm for artificial intelligence has been building towards a fever pitch in the past few years, but those feelings could get a bit more complicated in 2020.
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[C]ompanies and organizations are increasingly pushing tools that commoditize existing predictive and image recognition machine learning, making the tech easier to explain and use for non-coders. Emerging breakthroughs, like the ability to create synthetic data and open-source language processors that require less training than ever, are aiding these efforts.
At the same time, the use of AI for nefarious ends like deepfakes and the mass-production of spam are still in their earliest theoretical stages, and troubling reports indicate such dystopia may become more real in 2020.
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1. Machines will get better at understanding—and generating their own—speech and writing
A high-profile research org called OpenAI grabbed headlines in early 2019 when it proclaimed its latest news-copy generating machine learning software, GPT-2, was too dangerous to publicly release in full. Researchers worried the passably realistic-sounding text generated by GPT-2 would be used for the mass-generation of fake news.
GPT-2 is the most sophisticated of a new type of language generation. It involves a base program trained on a massive dataset. In GPT-2’s case, it trains on more than 8 million websites to understand the general mechanics of how language works. That foundational system can then be trained on a relatively smaller, more specific dataset to mimic a certain style for uses like predictive text, chatbots or even creative writing aids.
OpenAI ended up publishing the full version of the model in November. It called attention to the exciting—if sometimes unsettling—potential of a growing trend in a subfield of AI called natural language processing, the ability to parse and produce natural-sounding human language.
The resource and accessibility breakthrough is analogous to a similar milestone in the subfield of computer vision around 2012, one widely credited with spawning the surge in image and facial recognition AI of the last few years. Some researchers think natural language tech is rumored to be poised for a similar boom in the next year or so.
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3. AI will get more creative
Along those lines, GANs have also begun to fuel a burgeoning AI-generated art scene, which has inspired agencies and brands to explore more creative uses for generative machine learning. While this trend remains in its infancy (at least commercially), 2019 saw ad campaigns centered on GAN-generated imagery, the first commercial product designed by generative AI and breakthroughs in the ability of GANs to produce photo-realistic faces and landscapes.
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Experts expect GANs to grow more integral as creativity aids as companies like Adobe incorporate them into design software and other tools are built that make them easier for creatives without a technical background to use.
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5. Algorithmic ethics concerns will grow
Ethical questions about machine learning and algorithms were on everyone’s minds in 2019 as a growing movement of cross-disciplinary scholars sought to shift more academic focus to the technology’s social impact. Meanwhile, worrying headlines about prejudices baked into machine learning systems and AI-powered state repression demonstrated the necessity of such work.
This concern has also led to a phenomenon called “ethics washing,” wherein companies make a show of taking ethical issues seriously—without any concrete changes. The most reported notable example was Google’s creation of a largely powerless ethics board this year that was dissolved within a week after a fierce backlash.
Meanwhile, media took note of policymakers taking tangible action towards more ethical AI, proposing and passing new laws to govern the use of tech like facial recognition, and workers at big tech companies collectively pushing back against aspects of their employers’ business they deemed immoral.
This distinction is on track to grow in 2020 as empty talk fails to satisfy a growing movement looking for real change.
Link to the rest at Adweek