Currently, with the explosion of AI-generated art and the obsession with ChatGPT, the applications, as well as the concerns, of artificial intelligence (AI) highlight the potential and complexity of this technology.
Despite the creative AIs and their recent wave of popularity may seem overwhelming (almost as if they arrived "too early"), they represent an aspect of a broader trend: AI is actually transitioning from a theoretical phase to a practical one at a technological level.
The seemingly endless playbook of AI is working at full speed, turning potential scenarios into reality one after another.
For an AI development professional, these challenges are closely interconnected.
It is not enough to just develop efficient AI; it is crucial to do so in a way that the resulting effects are not harmful but contribute positively.
Consider, for example, that your revolutionary loan application relies on artificial intelligence and an advanced chatbot to determine which candidates receive approval for their loans. However, it does not provide an explanation to customers who did not get approval for the reason why their request was rejected.
If you do not establish expectations beforehand, you may find yourself facing a series of frustrated users. That is why one of the most significant challenges of AI is "lack of transparency." Artificial Intelligence, while being a powerful tool, can be difficult to understand and explain, especially when it comes to decision-making processes. This lack of clarity can lead to frustration and dissatisfaction among users, highlighting the importance of transparency in the use of AI.
An algorithm, no matter how intelligent, remains an algorithm. Machine learning, no matter how advanced, has not yet reached singularity level (yet). Therefore, any problem that an AI-based solution is designed to solve must be anticipated in advance. This allows developers to plan and program appropriate behaviors.
If you ask AI to "increase sales" or "optimize inventory," the results may not meet expectations.
How should your artificial intelligence behave when it encounters deviations from the expected patterns?
Just like a human would, of course: by calling its supervisor.
The value of artificial intelligence is determined not only by the cost of its development but also by the quality of the input and feedback it produces. In many cases, only a human can make an accurate assessment of these aspects.
No matter how advanced your algorithms are, they must be monitored and adjusted over time to ensure that new business or market circumstances are not making the quality of their data, and therefore the feedback, obsolete.
The value of AI tools lies in part in the technology's ability to reduce routine tasks, but that does not mean it eliminates the need for a human brain.
And it should not: AI performs at its best when integrated into existing business practices and applications that are largely the result of the human brain, not the other way around.
Undoubtedly, as tools evolve, the way we use them changes as well. You do not need to know how to use an abacus to be able to manage a calculator. However, when it comes to Artificial Intelligence, the level of ease is not yet that high.
Legislation should serve as the main safety net against the toxic use of technology.
But as society becomes more technologically savvy, our collective trust in the goodwill of technology companies diminishes in favor of the letter of the law, and regulations on AI are coming fast; the first round is already here, with the innovative European GDPR leading the way regarding data management, privacy, and security concerns.
An app that does not take this regulatory framework into account during development will have to be rebuilt once policies come into effect, and companies that act hastily (perhaps even industry giants) will face the possibility of having their entire business models outlawed, particularly regarding the protection of personal data.
Artificial intelligence is created, managed, and updated by imperfect and biased human beings.
Naturally, these flaws often end up in the fabric of technology and can be difficult to detect.
An evident lack of diverse data sources and adequate testing across a wide spectrum of the population can equally undermine AI, so it is crucial for developers and regulators to be particularly aggressive in identifying what is being overlooked.
Creative artificial intelligences based on deep learning are already operating in a variety of sectors, from music to writing to art.
The challenge intensifies when these creative AIs are capable of generating and spreading misinformation autonomously. For example, the GPT-3 algorithm has demonstrated this ability by convincing people that its artificially generated tweets on topics such as foreign policy and climate change were authentic.
This is problematic if AI systems that gather data fail to distinguish between truth and falsehood, compromising the quality of their datasets.
Due to the immense field of applications and the new solutions (or upgraded versions) to old problems that come with every blink of an eye, understanding exactly where and how artificial intelligence and machine learning can assist your business can be overwhelming.
Operationally? Logistically? During meditation breaks after lunch?
For many companies, the answer will be all of the above. But always in moderation: AI is a formidable tool with Swiss Army knife-like applications in every possible sector and vertical, but it is a tool that requires the human touch to be safe and useful. The true value of any AI always depends on how skilled its human managers are.
Few emerging technologies have become so ubiquitous in such a short time as AI, and even fewer have the potential to completely destroy humanity if we do not pay due attention.
Our team of experts is ready and available to guide you through the complexities of Artificial Intelligence and identify specific opportunities for your business. We are here to ensure that you can make the most of this revolutionary technology.