Following ethical practices in AI development is crucial for a fair world with less bias.
With the increase of AI’s presence in society, experts agree on the need for ethical boundaries applied during the creation and implementation of AI tools.
Companies use these principles to ensure responsible and fair creation and use of AI. Currently, there’s no governing body that writes and enforces these ethical rules, but many technology companies have their own AI ethics versions or AI codes of conduct and many governments are creating their own AI ethics frameworks.
Let’s learn more about the importance of responsible AI practices, current challenges, and how to make AI development more ethical.
AI ethics consists of principles used to make sure that AI technology is created and used responsibly to maximize safety, security, and humanness.
With an AI code of ethics, bias can be avoided and risks can be prevented. Frameworks designed by governments and codes of ethics implemented by companies that develop AI tech are the two main ways to better AI ethics.
AI ethics matters because AI is designed to expand or replace human intelligence. However, when technology is created for human life replication, the problems that could impede human judgment may also transfer into the technology.
So, AI technology created on improper or biased data may have bad consequences, especially for marginalized groups of people. Also, if AI algorithms and machine learning models are built too fast, it may make it harder for product managers and engineers to fix the learned biases.
On the other hand, if a code of ethics is implemented during the development process, further risks can be prevented.
There are several ethical challenges concerning AI. Here are some of the major ones:
AI technology uses data collected from internet searches, images on social media, comments on social media, online purchases, etc.
Although this enhances the personalization of the customer’s experience, it raises questions about the lack of consent from people given to companies that are using tools to access people’s personal information.
In 2022, the app Lensa AI used AI to make cool, cartoon-like profile photos from regular images of people.
Some people were critical of the app for not giving credit or funds to artists who made the original digital art that was used for the training of the AI.
And, billions of photos were allegedly taken from the internet without prior consent.
When AI fails to gather data that’s an accurate representation of the population, the decisions it makes may be biased.
If the results show prejudice against certain groups or individuals or aren’t aligned with positive human values such as truth and fairness, the consequences can be far-reaching as the AI further amplifies them.
One example of AI bias is from 2018 when Amazon was scrutinized for their AI tool for recruitment that downgraded resumes that included “women” in them.
The tool’s discrimination led to legal problems for the company.
Some AI models are big so the training results in major energy consumption.
Though research is ongoing to create energy-efficient methods for AI development, a lot more has to be done in the AI policies to address the ethical aspect of its environmental impact, especially its carbon footprint.
The high energy use contributes to greenhouse gas emissions and worsens climate change.
OpenAI researchers concluded that as of 2012, the power necessary for training AI models has doubled every 3.4 months. This industry, by 2040, will reach 14 percent of the global emissions.
To ensure ethical AI development, here are some important aspects to consider:
The code has to include the principles and values that the system is following and should be done via collaboration and inclusion of all involved parties (customers, stakeholders, employees, etc.).
AI systems need to be trained with diverse and inclusive data to prevent future biases and negative effects on groups or individuals.
The training should include representation of various races, genders, ethnicities, etc.
Training employees about the ethical aspect of AI and how to create and use it ethically is crucial to ensure they understand why AI ethics matters.
The education will equip them with skills to recognize and mitigate possible challenges.
Resolving privacy concerns is vital for ethical AI.
Privacy concerns may arise from the collection, processing, and storing of personal data. Systems need to comply with regulations set to protect data and secure its processing.
Privacy protection of sensitive patient data is essential in AI healthcare apps as well as in the collection and processing of photos collected from the internet and social media platforms.
Respecting human rights is necessary for responsible AI development.
AI systems need to be trained against bias and discrimination towards groups and individuals. Implementing responsible AI guidelines can help.
Companies need to be transparent about their AI systems, AI guidelines, the data they gather, the decision-making processes, and the algorithms they use.
This builds trust among customers and employees and prevents the exploitation of groups and individuals.
With the exponential growth of AI and its use in almost every industry, including vital industries like healthcare and security, AI ethics has become essential.
Companies and stakeholders need to implement adequate measures to maximize ethical practices and prevent bias, violation of human rights, and data breaches.
Building responsible AI helps companies better their responsibility and ensure ethical development and use of AI systems globally.
Are you curious to discover more about AI ethical practices and why they’re important for your company?
If the answer is yes, consult our experts at ArtHaus today!
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