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Artificial intelligence (AI) has seen rapid advancement, especially in recent years. It’s estimated that over 250 million companies (77%) are using or exploring AI in some capacity within their operations, and this doesn’t show any signs of slowing anytime soon. If anything, the use and availability of AI will continue to permeate in the months and years to come.
AI has been instrumental in powering innovations such as self-driving cars to behavioral pattern analysis, among numerous others. One area which has gained substantial notoriety in recent months is AI image generation.
Much like how ChatGPT and Bard have been centerpieces in discussions around AI text generation and coding, similar tools like DALL-E 2, Midjourney, and Stable Diffusion have been at the forefront of generating realistic images that would otherwise take much longer at the behest of a human photographer or graphic designer. Using text prompts and instructions, these tools can create detailed and thought-provoking images, artwork, and infographics that can be used for a variety of applications.
While it’s easy to look at AI image generation with rose-tinted glasses, it’s important to recognize some inherent ethical concerns that warrant further discussion. While many are lamenting the new creative potential of this technology, experts are cautiously advising that AI image generators be treated with care and that business leaders be mindful of the possible implications it can have on hardworking creatives. Unsupervised use of AI might lead many businesses to replace teams rather than augment them, while others may not be inherently aware of the cybersecurity threats that exist within these tools.
So how do you strike that right balance of improved efficiency with AI while safeguarding the creative and experienced minds of your team? This article will examine some of the key ethical benefits and considerations of widespread AI generation.
One of the most lauded aspects of AI image generators is their innate ability to make digital art, design, and creation more accessible.
Tools like DALL-E 2 essentially give users access to a full suite of intuitive elements that can allow them to create images with relative ease. It can be argued that this ‘democratization’ of creativity offers plenty of advantages for businesses and individuals who can leverage tools effectively.
From an environmental perspective, using AI tools could provide a sustainability and social responsibility boost. Entrusting image generation to computers may be much better for the environment than the collective emissions caused by human creatives’ journeys and the purchasing of new photography equipment. However, sustainable reuse and repurposing of tech can mitigate this problem.
In another positive, AI image and art generators allow anyone regardless of experience or skill level to draw and express creative freedom. Even amateur designers or novices with no natural art proficiency can explore their artistic side, which may have eluded them in the past. What’s more, experienced designers, artists, and content creators can rapidly iterate images that can supplement and support their projects. They can alleviate many of the inherent time pressures that persist when creating assets from scratch to tight deadlines, not to mention the time-consuming editing and refining processes.
There are also cost benefits associated with AI use; sole creators and companies alike can lower their outgoings on several paid services like stock photo libraries, storage tools, external hard drives, and so on. At its core, AI is an innovative technology that relies heavily on machine learning and deep learning. In other words, the more you use it, the more accurate and usable the output will be. By leveraging AI images successfully, it may enable new forms of visual media and creativity for your business to explore in greater depth.
In the interest of fairness, it’s imperative to look at the major concerns around the unregulated and unsupervised use of AI image generation. The potential for copyright infringement and plagiarism is huge; if you don’t exercise caution, you could be opening many proverbial ‘cans of worms’. Most AI tools are trained to recognize and utilize large datasets of images scraped off the Internet, without any mechanisms in place to alert them whether those images themselves are originals or whether they have been used unlawfully.
When prompted, AI tools may then replicate protected elements, symbols, styles, or typography, without any correct accreditation to their rightful owner(s). Even if a system doesn’t generate new pictures that directly copy the original artwork, photographs, or branding, they may produce similar or closely inspired derivatives, which can still be a legal concern.
Images generated by AI could – indirectly or directly – infringe on copyright source material which could affect compensation or remuneration for original artists. It doesn’t help that there is uncertainty and a lack of clarity around copyright laws that can sufficiently protect the works of original photographers and artists. Furthermore, disguising AI-generated works as originals only serves to deceive audiences that want to celebrate and champion human ingenuity and creativity.
There has never been a greater need for transparency and reassurance around AI generation. As it stands, the legal side is still evolving and adapting, but to preserve people’s livelihoods, these problems must be addressed and solved before long.
One other overt concern about AI’s rise to prominence is the employment implications that it could have on human creatives. If companies can churn out images, designs, and text with open-source tools, what does that mean for the experienced graphic designers, artists, and content creators of the world? What does it mean for their livelihoods?
Demand for human creatives may decrease with AI image generation’s continued evolution. Furthermore, companies may view AI generation as an alternative to fairly compensating human designers or photographers, which is morally questionable in the eyes of many.
Even if jobs aren’t replaced directly, the responsibilities of workers will unlikely shift and change. There is a belief that AI creative tools aren’t likely to replace human thought entirely; no computer can ever replicate the complexities and experiences of a person’s brain. However, it’s clear that workforce impact needs to be weighed heavily in professionals’ decisions on whether to adopt AI company-wide or take a more methodical, thoughtful approach to its integration.
Socially speaking, the imagery and content produced by AI systems is reflective of their training data. Biases and toxic perspectives have been evident when studying their outputs, and the continued lack of regulation means that this discourse will only continue to spread and perpetuate through generated art and imagery.
This can come in the form of race, gender, sexuality, disability, religion, or other biases and stereotypes, or amplified hateful, abusive, or violent images as ‘requested’ by users. With the AI tools’ lack of moral compass and ‘filter’, appropriating or casting harmful aspersions on cultures is easier, as is the potential spread of misinformation. Ongoing conversations around ethics, governance, and policies will be essential as adoption spreads.
AI image generation seems poised for major growth and applications across many industries. With this disruption comes plenty of risks for creators, companies, and policymakers alike, making the act of navigating this technology shift difficult.
Transparency and thoughtful legal guidance will be key, with clear disclosure of AI tool use and adherence to relevant data protection and copyright regulations. AI systems should be regularly audited and tested for problematic biases and validated that original artists are credited and compensated for their work when required.
This emerging technology still requires open, ongoing dialogue around its ethical application. That said, future possibilities are undeniably exciting, provided that more professionals can thoughtfully implement AI.
Disclaimer: The author is completely responsible for the content of this article. The opinions expressed are their own and do not represent IEEE’s position nor that of the Computer Society nor its Leadership.
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