The adoption of artificial intelligence (AI) also collects a pace, as well as complexity and its risk. Companies are increasingly aware of these challenges, however, road maps to solutions often remain mystery.
If the question is “How to move in these risks?” Echo with you, then this article will be a beacon in fog. We delve into the heart of the most urgent issues in artificial intelligence, supported by realistic situations, and developing clear and implemented strategies to safely overcome these complex terrain.
Reading to unlock valuable visions that can enable your work to benefit from the strength of artificial intelligence, all of which avoids the potentially paste.
1. Bias in decisions based on artificial intelligence
The unintended inclusion of the bias in artificial intelligence systems is a great risk with long -term effects. This risk arises because these systems learn and constitute their decision -making processes based on the data they are trained on.
If the data sets used for training include any form of bias, these prejudices will be absorbed and thus reflects in the system decisions.
Example: The algorithm in the UK level classification
To clarify, think about a real example that occurred during the Covid-19 pandemic in the United Kingdom. With the abolition of traditional exams at the level A due to health concerns, UK government It was used as an algorithm to determine students ’grades.
The algorithm boxes were made in different elements, such as the historical performance of the school, the student’s subject classifications, teachers ’assessments, and previous exam results. However, the results were far from the ideal.
Nearly 40 % of students got less than expected, which sparked a widespread violent reaction. The main issue was the excessive dependence on algorithm on historical data from schools to individual students.
If the school does not produce a student that has achieved the highest degree in the past three years, then no student will be able to achieve this degree this year, regardless of his performance or capabilities.
This condition shows how the bias of algorithms can produce unfair and perhaps harmful results.
Possible solution: the human approach in the episode
So, how can we avoid this predicament? The answer lies in human control. It is necessary to keep the people involved in decision -making operations from artificial intelligence, especially when these decisions can significantly affect people’s lives.
Although artificial intelligence systems can automate many tasks, they should not fully replace human rule and intuition.
The sectors that should avoid the only dependence on artificial intelligence decisions should be avoided
The so -called human approach in the episode is very important in the sectors in which the decisions based on artificial intelligence affect the individual life and society.
These sectors include:
- education: As it becomes clear from the United Kingdom, artificial intelligence systems should not be only responsible for the tasks of grades or the academic performance of students. The experience of the human teacher and his personal understanding of their students should play a decisive role in these cases.
- health care: Artificial intelligence has taken great steps in diagnosing diseases, planning treatment, and patient care. However, the possibility of wrong diagnosis or insufficient planning for treatment due to biases or errors in artificial intelligence systems emphasizes the necessity of human professionals in the final decision -making process.
- Employment and hr: Artificial intelligence is increasingly used to examine the appeal and predict a possible functional performance. However, reliance on artificial intelligence can lead to biased employment practices, and may overlook candidates with backgrounds or unconventional skills groups. The human approach in the episode guarantees a comprehensive and fair assessment of the candidates.
- Finance and lending: Artificial intelligence algorithms can evaluate creditworthiness, but they may unintentionally distinguish based on geographical location or personal spending habits, which can be linked to race or social and economic situation. In such scenarios, human rule is necessary to ensure balanced lending decisions.
- Criminal justice: Artificial intelligence is used to predict the hot points of crime and possible re -repetition. However, prejudice in historical crime data can lead to stereotyping and issuing unfair judgments. Human control can provide more accurate views and help prevent such injustice.
- Independent vehicles: Although artificial intelligence drives the operation of self -driving cars, it is very important that you have a person in the decision -making process, especially when the car must make moral decisions in incidental scenarios that cannot be avoided.
2. Violation of personal privacy
In the sophisticated digital world, the data has become a pivotal resource that pays innovation and strategic decisions.
The international data company predicts that global data will swell from it 33 Zettabytes in 2018 to 175 Zetabytes by 2025. However, this prosperous wealth of data also escalates the risks associated with personal privacy violations.
As this data range dramatically, the customer or employee data can be exposed in Lockstep. And when data leakage or violations occur, the repercussions can be devastating, which leads to severe reputation and possible legal repercussions, especially with the implementation of the most strict data processing regulations all over the world.
Example: Seamung data breach with ChatGPT
A vital clarification of this danger can be seen in the last Samsung accident. The global technology leader had a application a Ban ChatGPT When he discovered that employees had unintentionally detected sensitive information to Chatbot.
According to the Bloomberg report, the Special Source Code was shared with ChatGPT to verify the presence of errors, and the artificial intelligence system was used to summarize the meeting notes. This event emphasized the risks of sharing personal and professional information with artificial intelligence systems.
It was a strong reminder of all institutions that venture in the field of artificial intelligence about the prominent importance of solid data protection strategies.
Possible solutions: anonymous data and more
One of the important solutions to such a privacy is not to disclose his identity. This technology includes removing or modifying personal identification information to produce anonymous data that cannot be linked to any specific individual.
Companies such as Google made anonymous data on the cornerstone of privacy. By analyzing unknown data, they can create safe and useful products and features, such as completing the automatic search for search, all while maintaining the user identities. Moreover, unknown data can be shared from the outside, allowing other entities to take advantage of this data without endangering the user’s privacy.
However, anonymous data should be one part of the comprehensive data privacy approach that includes data encryption, strict access to access, and regular data use reviews. Together, these strategies can help organizations move in the complex scene of artificial intelligence techniques without endangering the privacy and individual confidence at risk.
[ Read also: 6 Essential Tips to Enhance Your Chatbot Security in 2023 ]
3. Ostrich and misunderstanding in making artificial intelligence decisions
Artificial intelligence is full of complications, and made more severe through the mysterious nature of many AI algorithms.
As prediction making tools, the internal works of these algorithms can be so complex that understanding how countless variables interact to produce prediction that can challenge even their creators. This ostrich, often called the “Black Box” dilemma, was the focus of investigation into the legislative bodies that seek to implement the appropriate checks and balances.
Such a complexity in artificial intelligence systems and the lack of transparency can lead to lack of confidence, resistance and confusion among those who use these systems. This problem becomes particularly evident when employees are not sure why the artificial intelligence tool has made specific recommendations or decisions and may lead to hesitation in implementing artificial intelligence suggestions.
Possible solution: AI is an explanation
Fortunately, there is a promising solution in the form Amnesty International can be explained. This approach includes a set of tools and technologies designed to make artificial intelligence models predictions understandable and interpretable. With interpretative AI, users (your employees, for example) can get an insight into the basic logical basis of the specific model decisions, identify potential errors, and contribute to improving the performance of the model.
example: EDTECH benefit from artificial intelligence for trustworthy recommendations
DLABS.AI team used this approach successfully during Edtech global platform project. We have developed an interpretable recommendation engine, which enabled the student support team to understand the reason for the program’s recommendation in specific courses.
AI, who is to explain and our customer, allowed us to dissect decision -making paths in decision -making, discovering accurate involvement issues, and refining data enrichment. This transparency in understanding the decisions taken by the “Black Box” models strengthened increased confidence and confidence between all parties concerned.
4. Legal responsibility is unclear
Rapid progress of artificial intelligence has led to unexpected legal issues, especially when identifying the decisions of the artificial intelligence system. The complexity of the algorithms often obscures the liability line between the company using artificial intelligence, artificial intelligence developers, and the artificial intelligence system itself.
Example: The Uber Self -driving incident
The issue of the real world that highlights the challenge is a A fatal accident involves an Uber self -driving car In Arizona in 2018, the car was hit and Illin Herzburg, a 49 -year -old infantry, was killing a bike on the road. This incident represents the first recorded death to include a self -driving car, which led to Uber’s suspension of technology in Arizona.
Investigations by the police and the American National Transportation Council (NTSB) were attributed primarily to destroy the human error. It was found that the safety driver in the car, Rafael Vasquez, was broadcasting a TV program at the time of the accident. Although the car was self -driving, Mrs. Vasquiz can take over in an emergency. Therefore, he was charged with neglected murder while Uber was exempt from criminal responsibility.
The solution: legal frameworks and moral guidelines of Amnesty International
To address the uncertainty surrounding the legal responsibility of making decisions from artificial intelligence, it is necessary to create comprehensive legal frameworks and moral guidelines that explain the unique complications of artificial intelligence systems.
These clear responsibilities of the various parties concerned must be determined from developers and users to companies that implement artificial intelligence. These frameworks and instructions should also address varying degrees of independence capabilities and decision -making capabilities of various artificial intelligence systems.
For example, when the artificial intelligence system takes a decision that leads to a criminal act, it can be considered a “perpetrator across another”, where the software programmer or the user can bear a criminal responsibility, similar to the dog owner asks their dog attacking a person.
Instead, in scenarios such as the Uber accident, where the normal procedures for the artificial intelligence system lead to a criminal act, it is necessary to determine whether the programmer knows that this result was a possible result of its use.
The legal status of artificial intelligence systems can change with its development and become more independent, adding another layer of complexity to this issue. Consequently, these legal frameworks and moral guidelines will need to be dynamic and update regularly to reflect the rapid development of Amnesty International.
Conclusion: Balancing risks and rewards
As you can see, artificial intelligence brings many benefits but also involves great risks that require careful study.
Through partnership with an experienced consultant specializing in artificial intelligence, you can move in these risks more effectively. We can provide designed strategies and guidelines about reducing potentials, and ensuring adherence to your artificial intelligence initiatives with the principles of transparency, accountability and morals. If you are ready to explore the implementation of artificial intelligence or need help in managing the risks of artificial intelligence, Set an appointment for a free consultation with our artificial intelligence experts. Together, we can harness the strength of artificial intelligence while protecting your organization’s interests.
