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“AI and chatbots are a revolution in software and quantum computers are a revolution in hardware”¹. This statement come with a warning “when they get together, it could be terrifying for humanity”². Artificial intelligence is receiving attention from all over the place. Regulators are starting to develop frameworks to protect the people from AI. Europe just issued an interesting initiative³, but what is at stake here? Quantum computers are going to revolutionize AI and lawmakers need to get ready for that.

Quantum computers operate based on the principles of quantum mechanics. Unlike classical computers that use bits to store and process information, bits those which can be only in two states – zero or one, quantum computers utilize quantum bits, or qubits, which possess the incredible ability of superposition. This means that a qubit can exist in multiple states simultaneously representing both zero and one at the same time. This is not just a small advancement in the basis of computation, it’s an incredibly large leap that provides possibilities for solving highly complex problems that modern computers are limited to. Thus, the power of quantum computers lies in their capacity for parallel computation, exploring multiple different states and possibilities simultaneously, which result in solving complex problems much faster than classical computers⁴.

It has a history dating back to the early 1980s when physicists Richard Feynman and Yuri Manin introduced the revolutionary concept of quantum computation and envisioned a new kind of computer that could leverage the principles of quantum mechanics to tackle complex problems beyond the capabilities of classical machines. However, it wasn’t until the 1990s that significant breakthroughs in this field began to emerge when a mathematician named Peter Shor unveiled an algorithm that that could efficiently factor large numbers. Such fact is critical because factoring numbers plays a crucial role in many encryption methods used to protect sensitive information in our digital world today⁵. Shor’s algorithm opened up a whole new realm of possibilities and instigated both excitement and concerns among scientists as it showed how powerful quantum computers could be in breaking the encryption systems we currently rely on. So, throughout the last couple of decades, researchers from different leading technology companies started exploring different ways to build practical quantum computers⁶.

As an example, 2019, Google showed the world quantum processor Sycamore. Sycamore tackled a complex math problem that would’ve taken classical computers approximately 10,000 years to solve in 200 seconds⁷. In 2020, IBM took the lead by producing the IBM Q System One, the very first fully integrated quantum computer designed for commercial use consisting of the quantum hardware, cryogenic systems for controlling extreme cold temperatures, precision electronics, quantum firmware and resources for coupling with classical computation⁸.

In order to make quantum computing a reality, there’s a necessity to manipulate and control those qubits effectively and that’s where various physical systems come into play like atoms, ions, superconductors, integrated circuits and even photons. These systems are carefully crafted and engineered to preserve the delicate quantum states of the qubits, allowing operations to be performed on them. Firstly, and similarly to classical computers’ logic gates, quantum computers also have quantum gates. These gates are like the conductors of qubits and manipulate the quantum states of qubits to carry out specific computation by applying a sequence of these gates to a group of qubits to solve problems⁹.

However, there is more: Quantum computing has another edge and incredible characteristic denominated quantum entanglement¹⁰. Summarizing, when qubits become entangled, their fate become intertwined regardless of how far apart they are. It’s like they’re in constant communication, no matter the physical distance between them allowing qubits within a quantum computer to establish intricate relationships. They can work together processing vast amounts of information simultaneously, giving quantum computers additional humongous potential to solve certain problems, way faster than classical computers.

So, with qubits superposition, gates and entanglement characteristics, the future of quantum computing looks bright. It has shown impressive performance in many areas where classical computers struggle, for example, complex optimizations and super speed at factorizing immense numbers. In areas like medicine, simulations aimed at understanding the full functioning of the human body have been limited by the available computational power and precision whereas quantum computers are naturally suited for simulating the behaviors of tiny particles and quantum phenomena by simulating atoms, molecules, and small particles of materials. Quantum computers simulations can provide valuable insights in chemical reactions and material properties and this capability has significant implications for drug discovery, for example, where quantum simulations can greatly accelerate the search for new drugs and optimize molecular interactions, potentially transforming the pharmaceutical industry¹¹.

Now, in relation to machine learning and artificial intelligence, quantum computers may bring a whole new ceiling of innovation. According to physicist Michio Kaku, these quantum machines have the power to revolutionize the AI landscape.¹² AI’s chatbots are impressive at generating texts that sounds like it’s coming from a real human, but they still have their limits. These chatbots rely on recognizing patterns in the training data rather than truly understanding the meaning behind the words, so they do not know the difference between correct and incorrect, which means that it can lead to misinformation. Many experts have raised serious ethical concerns about these AI systems¹³. However, quantum computing may be able to address some of these limitations by leveraging the power of qubits as, for example, entangled qubits can instantly influence each other, enhancing computational efficiency, while quantum interference can guide quantum systems toward optimal solutions, making quantum computers well-suited for solving these complex problems. Integrating quantum computing and AI could have transformative implications, exponential speed to accelerate machine learning, model training, and enhance natural language processing. They could also potentially act as fact checkers, ensuring accurate information, weighting out false information, and providing a valuable verification factor for AI software¹⁴.

Regardless, with the impending rise of quantum computing, we should soon see quantum powered AI chatbots, lightning fast, super-efficient ones that can double check information for accuracy. AI and quantum computers together will surely be able to handle complex tasks, understand contexts, and give responses in the world of science such as discovering and designing new materials with sophisticated properties by doing elaborate quantum simulations.

Also, before wide adoption of quantum computers, there is a need for standardization and development of more complex encryption techniques to eliminate privacy risks. Measures such as cyber security and regulations addressing the appropriate use of quantum computer applications, considering ethics and safeguarding privacy are necessary before common use of such technology. Additionally, since quantum computing can have significant implications for artificial intelligence and machine learning, it is crucial to ensure responsible use.

In this sense, we see the first wave of regulations trying to catch up with AI¹⁵. The European Parliament is proposing an “AI Act” that would work on establishing rules focusing on protecting citizens against AI misuse. Among potential prohibitions would be: biometric categorization systems that use sensitive characteristics (e.g. political, religious, philosophical beliefs, sexual orientation, race); emotion recognition in the workplace and educational institutions; social scoring based on social behavior or personal characteristics; AI systems that manipulate human behavior to circumvent their free will.

For AI systems classified as high-risk (due to their significant potential harm to health, safety, fundamental rights, environment, democracy and the rule of law), clear obligations were agreed.

The agreed text will now have to be formally adopted by both Parliament and Council to become EU law. Parliament’s Internal Market and Civil Liberties committees will vote on the agreement in a forthcoming meeting.

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