How Talented is Creative Artificial Intelligence?
Imagine an artificial intelligence crafting poetry that touches your soul, designing clothes tailored to your unique style, or composing music rivalling your favourite artists. This isn’t mere fantasy; this is the sharp end of AI that is focused on creating brand new content, the realm of generative artificial intelligence. While generative AI keeps creating content, its sibling, machine learning, grows ever more intelligent by analysing mountains of data to predict and decide. They are reshaping our world together, and their future is filled with exciting possibilities.
Artificial intelligence (AI) has made staggering strides in recent years, infiltrating new and thrilling domains. Generative AI and machine learning stand at the vanguard of this transformation, with the potential to revolutionize our reality.
Think of generative AI as a creative chameleon, seamlessly adapting to diverse artistic mediums. It can compose music mimicking that of Mozart, write smash news articles like experienced journalists, or generate lifelike images that one may think are photographs. But how does it achieve this? By delving into vast datasets with machine learning algorithms, discerning underlying patterns, and utilising this knowledge to create entirely novel content. Such content can be in various forms, including text, images, music, and even design.
Let’s delve into the applications of generative AI…
Artificial Authors: Capable of penning news articles, blog posts, novels, and even poetry.
Artificial authors can create texts indistinguishable from human-written ones when given specific topics or keywords. These texts can be used for a variety of purposes, such as blog content, advertising copy, e-commerce product descriptions, and even press releases.
This in-depth article you are reading is also the fruit of a collaboration between the actual author and artificial intelligence in certain sections. We may even showcase poetry tailored to this very article:
(Command: Write a 4-line poem about the future of creative AI)
Lines of code, a canvas vast,
AI’s hand, a brush at last.
New forms bloom, unseen before,
Human and machine, explore.
(written by Gemini)
In circuits’ dance, the future we espy,
Creative AI, where dreams defy,
Art’s new frontier, where algorithms fly,
Innovation blooms ‘neath digital sky.
(written by Chat GPT)
Artificial composers: Crafting personalised music, soundtracks, and even mainstream hits.
Drawing from music theory and compositional techniques, artificial composers fashion tunes tailored to specific genres or moods. The resulted music can be used in various ways such as background music, commercial jingles, video games, and even cinematic soundtracks.
The YouTube channel AInfinite offers 24/7, endless AI-generated visuals, videos, and music.
Artificial designers: Designing products, logos, and even buildings.
Guided by principles of aesthetics and functionality, AI designers are able to conceive designs optimised for distinct purposes and target demographics. These designs can be used in development, marketing, branding and advertising, and architecture.
– What benefits will creative AI, which we will increasingly experience in such areas of use, offer us?
Firstly, personalised content and products come to mind. Creative AI can produce content and products tailored to users’ preferences and past behaviours. This customisation enhances user engagement, relevance, and overall satisfaction.
By automating creative tasks such as content generation, creative AI frees up the time and resources of professionals. This allows them to focus on more complex and strategic endeavours, leading to increased productivity and innovation. Automating creative work saves time and resources.
Creative AI can assist scientists and designers in discovering new ideas and solutions. Whether it’s designing new molecules, developing medicines, or innovating products and services, AI contributes to scientific and technological advancements by facilitating novel insights and solutions.
– So, what are the barriers to creative AI becoming more useful in modern life?
The primary critique directed towards creative AI-generated content, particularly in the realm of artistry, revolves around its originality. It’s imperative that AI-produced content doesn’t merely replicate existing data, but rather introduces fresh and innovative ideas. This underscores the necessity for creative AI models to be engineered with a greater emphasis on originality and innovativeness.
Nevertheless, despite all advantages offered by creative AI, we must keep in mind its potential for misuse. Creative AI is perceived as a potent tool that can be wielded to fabricate convincing fake news and propaganda, effectively manipulating public opinion and facilitating political agendas through disinformation.
Deepfake, an AI-driven technology that alters the visual and auditory aspects of a person in video or audio recordings to fabricate false content, utilises sophisticated machine learning techniques to superimpose a person’s likeness onto another video or mimic their voice.
Through the manipulation of images and voices of individuals in multimedia recordings, Deepfake can be exploited to produce counterfeit content for nefarious purposes such as extortion, disrepute, and political manipulation. Instances might also arise where creative AI is leveraged to forge credentials for identity theft or falsify financial documents for fraudulent activities.
These examples merely scratch the surface; the spectrum of potential misuse of creative AI is considerably vast and intricate.
One approach to mitigate these risks involves developers and users of creative AI technologies placing a strong emphasis on transparency, and adhering to ethical principles governing the utilisation of such technologies. It is also crucial to educate users on discerning between AI-generated content and authentic material, enact legislative measures to forestall AI abuse, and develop technological solutions like Deepfake detection systems.
While using powerful technologies like creative AI and machine learning, we must consider ethical concerns. Responsible utilisation of these technologies entails maximising their benefits while minimising associated risks.
At this point, another pivotal focus area is the ethical dimension of artificial intelligence. Currently evolving into a distinct field within philosophy, AI ethics comprises a framework of principles guiding engineers, policymakers, and other stakeholders in ensuring the responsible development and deployment of AI. This necessitates adopting a prudent, secure, humane, and environmentally conscious approach to AI advancement.
Basic Principles of Artificial Intelligence Ethics
Beneficence: AI systems must be developed with the intention of benefiting individuals and society at large.
Fairness: AI systems must uphold principles of fairness and impartiality, refraining from favouritism or discrimination against any particular group or individual.
Autonomy: Individuals should retain autonomy and agency over their interactions with AI systems, including decisions regarding data collection, tracking, and usage.
Openness: AI systems should be transparent and explainable, enabling humans to comprehend how they operate and make decisions.
Security: AI systems must be designed in a safe and reliable manner, to ensure protection against cyber threats, unauthorized access, and misuse.
Creating more ethical AI necessitates a thorough examination of the ethical requisites of policy, education, and technology. Regulatory frameworks may ensure that technologies serve the betterment of society while averting potential harm. Governments worldwide have already commenced implementing policies for ethical AI, stipulating guidelines for companies to address legal issues, such as instances of bias or other forms of harm, should they arise.
It is imperative for everyone engaging with AI to grasp the risks and potential adverse effects stemming from unethical AI or one that is used to produce fake content. Providing accessible resources for understanding and addressing these risks can help mitigate their impact.
While employing technology to identify unethical behaviour in another technology may initially seem paradoxical, AI tools can effectively be used to discern the authenticity of various media formats, such as videos, audios, or texts, including identifying hate speech on platforms like Facebook. These tools excel in detecting unethical data sources and biases more efficiently than humans, thereby enhancing overall efficacy in addressing such issues.
Machine Learning
Machine learning is a specialised subset of artificial intelligence that empowers computers to learn through analysing data and identifying patterns, without being programmed. It forms the cornerstone of creative AI technologies. It is analogous to the way a child learns through playing games and collecting experiences. Machine learning algorithms construct models from vast datasets, and use these models to predict or categorise new information. For instance, a model trained on Beethoven’s compositions may generate a novel symphony, or one inspired by Van Gogh’s artwork might produce a new painting.
Machine learning begins with data -numbers, images, text, financial transactions, photographs and paintings of individuals, kitchen gadgets, maintenance records, time sequence data from sensors, or even sales reports. The data is gathered and prepared to serve as the foundation for training a machine learning model. More data means better programming.
Subsequently, developers select the machine learning model they will use, feed in the data, and allow the computer model to train itself, by recognising patterns and generating predictions. In time, human programmer may adjust the model and its settings in order to refine its accuracy. For example, if an algorithm tasked with generating recipes proposes an unusual combination like “chocolate chicken cake,” developers might step in.
A portion of the data is reserved and not included in the training phase. This set, known as evaluation data, is used to assess the model’s accuracy with unfamiliar data. The outcome is a versatile model that, once perfected, can be applied to various datasets in the future. This refined model is then utilised to enable creative AI to generate innovative and original content.
The last paragraph comes from chat GPT, exactly as it is:
(Command: What could be the last paragraph of an article on machine learning, creative AI and their future?)
“As we navigate the evolving landscape of machine learning and creative AI, it becomes increasingly apparent that the future holds boundless possibilities. As these technologies continue to mature, we must remain vigilant in addressing ethical concerns, ensuring transparency, and fostering collaboration between humans and machines. With the right approach, the integration of machine learning and creative AI promises to revolutionize industries, enhance human creativity, and ultimately redefine what it means to innovate in the digital age. Embracing this future with thoughtful consideration and a commitment to responsible development will undoubtedly lead us toward a future where artificial intelligence augments our capabilities, enabling us to tackle challenges and unlock opportunities beyond our current imagination.”
Images used in this article were generated by AI.
REFERENCES
- 1. https://mitsloan.mit.edu/ideas-made-to-matter/machine-learning-explained
- 2. https://plato.stanford.edu/entries/ethics-ai/#Intr
- 3. https://gemini.google.com/
- 4. https://chat.openai.com/