The presence of Artificial Intelligence (AI) in various aspects of our lives is a relatively recent phenomenon. Around twenty years ago, AI began to play an active role in translation and localization. This marked a significant leap in the translation industry, radically altering the role and tasks of translators. And these days, AI allows you to do anything from creating a unique Dragon Slots login to launching your own app. Keep reading to know more about it.
AI Revolution in Writing Professions
About ten years ago, AI evolved to translate content and generate text independently. This led to a “revolution” across a wide range of professions associated with writing, such as journalism, law, technical writing, copywriting, public relations, advertising, marketing, and more.
Among the latest breakthroughs in AI is the generation of images from textual descriptions. One notable event occurred in March 2023, when an alleged photograph of the Pope wearing a puffer jacket from a well-known fashion house spread across the media. It later turned out that the strikingly realistic image was created by AI (specifically, the Midjourney neural network), not by paparazzi.
The Impact of AI on Professions
Every time AI reaches a new developmental milestone, discussions arise about the “extinction” of certain professions, declining demand for certain services, and their sharp price reductions. However, professions do not disappear. Instead, AI continues to influence a wide range of sectors — from law and industry to medicine and banking.
Let’s explore the advantages and disadvantages of AI and its impact on communication models, work processes, and decision-making across different fields.
Ethical Aspects of AI Use
The use of AI raises a number of ethical issues and challenges. Here are some of the most significant ethical aspects of AI application.
Responsibility and Accountability
One of the key ethical questions surrounding AI use is that of responsibility and accountability. Who is responsible for errors or harm caused by an AI system? Should it be the AI system’s developer, the user, or someone else? Clear rules and protocols must be established to define responsibility and accountability in AI usage.
Data Privacy and Security
AI systems often work with large volumes of data, including personal and confidential information. Privacy concerns are closely linked to technologies like Deepfake, which can generate audio and video content.
One early, harmless example of this technology was the sudden appearance of Henry Cavill in the 1968 James Bond movie The Living Daylights. Cavill’s face was superimposed over Timothy Dalton’s, maintaining his signature expressions and gestures.
However, Deepfake technology can turn its participants into crime victims. Today, there are numerous cases of fraud using the images of both celebrities and ordinary citizens. The goal is often property fraud, theft of funds, and other crimes.
We must ensure the security and confidentiality of this data to prevent unauthorized use or distribution. This requires the development and implementation of effective security measures and clear rules for handling and storing data.
Bias and Discrimination
AI systems can be biased if they are trained on data containing elements of bias or discrimination. For example, a facial recognition system used in an airport might be biased against people of African, Arab, or Asian descent. Gender bias is also a possibility, with women’s faces often being recognized less accurately.
According to statistics, the error rate for facial recognition systems when identifying white men is 0.8%. Meanwhile, the error rate for recognizing Black women reaches 34%.
This research was conducted by the Massachusetts Institute of Technology (MIT) in 2018, with results published in the paper Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification.
The authors attribute the high error rate to the use of homogeneous data. The system was predominantly trained on data about white men, leading to discriminatory results.
Methods must be developed to identify and prevent bias in AI systems, ensuring that the data used to train AI is more representative.
Autonomy and Free Will
AI systems can make decisions and act autonomously, without direct human intervention. This raises questions about autonomy and free will. Should AI systems have the right to make decisions independently, or should they always be under human control? Clear rules and protocols need to be established to define AI systems’ autonomy and free will.
Transparency
AI systems can be complex and difficult to understand, making them opaque. Therefore, methods must be developed to ensure transparency in AI systems, so people can understand how they work and why certain decisions are made.
Social and Economic Consequences
The use of AI can have significant social and economic impacts, including job losses, changes in employment structures, and income inequality. Governments must develop specific programs to mitigate these consequences and ensure that the benefits of AI are distributed fairly and evenly.
The ethical aspects of AI use are crucial and require careful consideration. We need to establish clear rules and protocols to determine responsibility, ensure data privacy and security, and more. Only then can we maximize the potential of AI and guarantee that its use is fair, safe, and ethical.
AI Applications Across Industries
Law
In the legal field, AI is used to analyze large volumes of data, identify patterns, and predict the outcomes of court cases. AI systems can analyze legal decisions, laws, regulations, and case outcomes.
AI can identify patterns much faster than humans, speeding up the decision-making process in court cases, allowing judges and lawyers to focus on more complex and important matters. For instance, in 2019, the U.S. Supreme Court used AI to analyze data from tax-related court cases, helping the court identify patterns and make more informed decisions.
AI can analyze data more accurately than humans and uncover patterns that may not be obvious. This can improve data analysis accuracy and prevent errors in court rulings.
AI can also automate many tasks currently performed by lawyers and judges, such as data analysis and document preparation. This can reduce legal service costs and make them more accessible. For example, in 2019, “Rocket Lawyer” began using AI to automate the preparation of legal documents, reducing legal service costs and making them more affordable for clients.
However, there are certain downsides to using AI in law. AI requires access to large amounts of data, including confidential and personal data. This can create risks for data privacy and security if proper protective measures are not implemented.
Moreover, AI systems can be biased if trained on data containing biases, potentially leading to unjust or discriminatory outcomes in court cases.
Thus, while the use of AI in law offers many advantages, it also presents challenges that require solutions. It is important to ensure data privacy and security, prevent bias in AI algorithms, and develop new legal norms and standards for regulating AI usage.
Industry
In industry, AI is used to optimize production processes, forecast demand, and manage supply chains. This allows businesses to increase production efficiency, reduce costs, and improve product quality.
AI can analyze production data and identify areas for efficiency improvement. For example, AI can determine optimal equipment settings to reduce downtime. Siemens used AI to optimize production at its plant in Germany, increasing productivity by 20% and reducing energy consumption by 15%.
Similarly, BMW used AI to improve product quality at its plant, reducing defective products by 25%.
At the same time, AI must be integrated with existing production systems to ensure efficient use of data and equipment. Such integration can require significant investments. General Electric, for instance, spent several million dollars integrating AI with existing production systems at its U.S. plant.
AI systems must also be safe and reliable to prevent accidents and production failures. Another challenge is the need for employee retraining to work with AI technologies.
Thus, while AI offers numerous advantages in industry, it also creates problems that must be addressed. Effective integration of AI with existing production systems, the safety and reliability of AI systems, and worker retraining are all essential.
Translation and Localization
In the field of translation, AI has long been used for automatic translation of written text and speech. The widespread use of AI in both translation agencies and by individual translators began around 2010, when agencies started mass adoption of CAT programs (computer-aided translation).
CAT programs, based on the principle of multi-component authoring, allow texts to be viewed as a set of fragments, inserting already-translated parts into new texts. This accelerated the translation process, improved accuracy, and reduced translation costs.
AI use in translation offers both advantages and disadvantages. Quality and accuracy need to improve, context recognition must be enhanced, and new standards and protocols for evaluating translation quality should be developed.
Technical Writing
In technical writing, AI is used to automatically create technical documentation, speeding up document creation, improving accuracy and quality, and reducing writing service costs. For example, IBM has long used AI to automatically create technical documentation on its website, reducing development time by 80%.
However, using AI in technical writing also has significant drawbacks. AI might miss complex technical nuances and context, creating documentation with errors or insufficient detail. Additionally, AI-written technical texts might be too templated and not tailored enough to user needs, reducing their effectiveness.
Thus, while AI brings many benefits to technical writing, human control and oversight are still necessary.