Over the past ten years, we have embraced Siri, Tesla Autopilot, Grammarly, Amazon Alexa, and Google Assistant. With the emergence of even more AI content creation tech, ChatGPT in particular, the conversation is running hot across digital marketing, design, writing, psychology, education and tech, discussing what it means for the future of creativity, information and, well, humanity in general!
AI learning technologies have already changed the way we create.
- You can transcribe and analyse audio and video content with Descript.
- Canva uses machine learning to make personalised design recommendations and is beta-testing Magic Write in their platform.
- Wav2Lip generates realistic lip-syncing audio for videos.
- Runway ML can generate or manipulate images, video and sound using cutting-edge machine-learning models.
While we don’t believe a Terminator 2 style takeover is imminent, with the recent developments, it is important to weigh the the pros and the pitfalls of this new frontier.
How AI learning works
There are three primary types of AI learning: supervised, unsupervised, and reinforcement learning. Each class has advantages and disadvantages, depending on the problem you’re trying to solve.
Supervised Learning works for classification problems and means providing labelled data to the computer to ‘learn’ from and predict the correct result. For example, it’s programmed with images and information on cats and dogs to understand how to distinguish them.
Unsupervised Learning is where unlabeled data is input, and the software finds patterns and relationships within the data. The software has to identify similarities and differences in the data without any labeled data to guide it, e.g. it’s used in analysing customer behaviour patterns based on their purchasing habits.
Reinforcement Learning centres on decision-making and learns by interacting with the environment and receiving rewards or penalties for specific actions. When you hit the like or dislike button and provide feedback on ChatGPT, the tech knows to maximise thumbs up and minimise negative feedback. This software learns to make the best moves to ‘win’ through rewards and avoid penalties for losing.
Harnessing the potential
Increased efficiency and productivity are an AI content creation win by automating routine tasks and processes, freeing up our time and resources at home and work. AI can analyse massive amounts of data compared to humans and detect things we might overlook, enabling faster, more informed decisions.
Many are hailing ChatGPT as a content creation time saviour for idea generation, research, planning and writing. It provides support for content creators in multiple languages and can be trained to understand a content creator’s style, tone, and preference through directive prompts.
AI is already leveraged to improve marketing and increase customer engagement by examining user preferences and behaviour and tailoring products and services for personalised and satisfying user experiences. Using AI tech to analyse and interpret complex scientific data will likely lead to discoveries and insights, including disease treatments and weather prediction.
So much good is possible, but as Erik Brynjolfsson, director of the MIT Initiative on the Digital Economy and author of “Machine, Platform, Crowd: Harnessing Our Digital Future,” said, “We need to work aggressively to make sure technology matches our values. This can and must be done at all levels, from government to business, to academia, and to individual choices.”
Causes for concern
One primary concern is AI displacing specific jobs as machines become increasingly capable of performing our tasks. While some experts believe that new jobs will emerge, like AI development and maintenance, significant labour market disruptions will continue to occur like it did for car manufacturing.
ChatGPT-produced content, fed through paraphrasing AI tools like Quillbot, is disrupting classrooms, sparking a call for the return of in-person assessments.
“While the tool may be able to provide quick and easy answers to questions, it does not build critical-thinking and problem-solving skills, which are essential for academic and lifelong success,” said Jenna Lyle, a spokesperson for the New York City Department of Education, in a statement to The Washington Post.
Some schools have blocked these programs on their servers, and to counter plagiarism, some sites like writer.com have created AI-content detectors, GPTZero, an antithesis to ChatGPT.
AI systems perpetuate and amplify existing biases and discrimination when trained on partial data and that of developers’ preferences, posing severe ethical implications. Statistical inaccuracies have been reported, and platforms’ terms and conditions state they can modify and use your content however they wish, for which there is no easy recourse, making your creations available for use and repurpose.
Privacy and personal data collection are real concerns as AI systems become more widespread. With cyber threats already a massive problem, more personal information will be available for theft and misuse when systems are hacked or compromised.
When decisions are left to AI, responsibility and accountability become issues that can have dire consequences in medical diagnosis and autonomous vehicles. Then there’s the worry that these systems will become powerful enough to pose an existential threat to humanity, either unintentionally or maliciously.
Staying human
Future outcome predictions are rife, and how this all plays out is up to us.
Our emotions are far more profound than our intelligence and are the driving force of our creativity. Our sentience and consciousness are what makes humans superior to any machine. AI technology may seem intelligent, and it certainly is, but it’s not conscious or aware.
One cannot be sentient without biologically experiencing the world around us. There is no “ghost in the machine” because sentience requires natural or artificial biology. Where the slope will get slippery is the human integration with AI.
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