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AI coding has become a game-changer in boosting developer productivity, optimizing workflows, enhancing code quality and saving costs via efficiencies.
But despite these key advantages, is AI coding unethical?
Already 18% of businesses have started using AI for software engineering tasks – and this number is sure to grow. Before you go all-in with AI coding, it’s vital to consider the ethics surrounding it – from algorithmic bias to job loss and more.
Here we’ll spark the discussion around responsible AI development by exploring ethical concerns, best practices and how TECLA advances AI ethics.
What Does AI Coding Involve?
AI coding involves using a generative tool to automatically create or complete code. It may also be used to detect errors or optimize code.
The idea behind these tools is to improve developer productivity and efficiency. In fact, AI may reduce time-to-completion for writing code by 35-45%. As a result, this frees up developers to focus on more complex or satisfying work – as reported by 74% of developers.
Keep in mind that AI coding tools can’t come up with technical solutions. Yet, they can support a developer’s writing process. They’re based on deep ML algorithms that build “neural networks” through vast datasets of source code. Some popular options today include Copilot, TabNine, Ask Codi and more.
Common Use Cases
AI coding tools are especially useful when working with large or repetitive codebases. This is often the case for enterprise industries such as healthcare, fintech, logistics, manufacturing and retail. The most common use cases for AI coding tools include:
- Code generation
- Bug detection
- Code optimization
- Security scanning
- … and more!
Why AI Ethics Matter
AI coding may have advantages for developers and technical teams. At the same time, companies should be intentional about how they integrate AI into their business processes.
In essence, understanding and addressing the ethical concerns of AI is a matter of corporate responsibility. It’s essential to “do AI right” to stay within your company values and reduce the risks of lawsuits, consumer disapproval and/or loss of reputation.
Ethical Concerns in AI Coding
How is AI coding unethical? Let’s take a deeper look into AI ethics that may impact your development teams.
Bias in AI Algorithms
Biases in training data can unintentionally create biases in the algorithm itself. Take for example:
- Google ads displayed high-paying job openings to men more often than women.
- iTutor Group’s AI recruitment tool auto-rejected job applicants due to age.
- AI-suggested emojis have reinforced negative racial stereotypes.
Understanding the limits of training data is key to improving fairness in AI algorithms.
AI and Job Displacement
32% of IT workers believe AI will “help more than hurt” their careers. Even so, the risk of job displacement in technology and more may be significant. The U.S. Bureau of Labor outlines a list of jobs at high risk of displacement from automation, with as many as 47% at risk by the mid-2030s.
AI Accountability & Ownership
Who is responsible when AI does harm? The question of ownership and accountability is another ethical (and legal) dilemma. The courts recently decided that AI-generated art can’t be copyrighted, as there’s no human creator. What about the publishing of AI-generated fake news or the crashing of a self-driving car? Without clear ownership of AI in our current laws, it’s difficult to know who’s responsible for these negative outcomes.
Security & Privacy Risks
The question of security and privacy is also top of mind. The worry is that AI surveillance isn’t accurate, especially for certain groups of people. Police using AI facial recognition to find suspects, for example, has led to countless examples of wrongful arrests and convictions.
At the same time, private information used by AI may be stored by institutions without consent or regulation. For instance, one in two Americans has their image stored on a law enforcement facial recognition database. Yet, privacy risks could apply to any organization gathering data – from hospitals to local retailers.
Sustainability
What’s more, AI models consume a lot of water to handle computations. Experts predict that a large data center consumes the water equivalent to 4,200 people per day. That’s why businesses should consider calculating their water footprint when using AI coding tools.
The Case for Ethical AI Development
Given the ethical concerns of AI, it’s more important than ever for business to develop a framework for responsible AI coding.
Benefits of AI Coding
The business world is buzzing with the benefits of AI coding. Some reasons why technology teams leverage AI tools include:
- Elevating developer productivity and efficiency
- Optimizing workflows
- Enhancing code quality
- Savings costs
- Freeing up time for more complex work
What’s more, usage of AI coding tools is becoming more prevalent, with 92% of developers using them either at work or in their personal time.
Best Practices for Responsible AI Coding
Fortunately, your developers can still reap the benefits of AI coding tools while minimizing negative outcomes. Let’s discuss how our experts at TECLA are harnessing ethical AI development practices.
1. Transparent Disclosure & Documentation
AI usage and development should always be explainable. Our engineers always disclose if AI coding tools were used and discuss any limitations to support AI transparency.
What’s more, when building AI, our experts create robust documentation about the training data, architecture and model, as well as all decision-making processes.
2. Include Code Review & Continuous Monitoring in Lifecycle
Whenever our teams integrate AI tools, we include code reviews and continuous monitoring into the lifecycle. Doing so provides clear oversight of the code and opportunities to flag issues before (and after) going live.
3. Use Industry-Leading Privacy Standards
Our engineers at TECLA also follow all applicable AI regulations, data practices and industry standards. Some essential practices to safeguard privacy include user consent, data minimization, data encryption and anonymization.
4. Clarify AI Accountability & Ownership in Contracts
Additionally, we make the code ownership and accountability clear within our initial hiring contracts. We also detail any licensing and attribution requirements. Most frequently, our recommendation is for clients to retain ownership of the code, with full disclosure of any use of AI.
5. Explore GreenTech Practices
Our tech professionals are at the cutting edge of greentech practices, too. We recommend ways to reduce energy waste across your digital projects, as such:
- Using AI coding for only the most high-impact areas
- Optimizing algorithms for energy efficiency by reducing computational demands
- Improving data efficiency and quality to reduce cloud storage demands
- Track greentech initiatives for better understanding of potential impacts
6. Recommend Clients Create an AI Ethics Framework
Finally, if you’re developing an AI-powered solution, we recommend creating a framework for your AI and machine learning ethics. Doing so can help you deploy AI within your corporate values and stakeholder expectations.
For example, if your new internal AI tool will create job redundancies, your AI ethics framework may assure employees of your commitment to upskilling and reskilling programs.
How TECLA Helps Companies Build Ethical AI Solutions
At TECLA, we strike the balance between creating next-gen AI solutions and adhering to ethical AI development standards — here’s how.
1. Access to Ethical AI Experts
Our full network of elite developers is committed to responsible AI coding. They’re well-versed in AI ethics and follow best practices such as documentation, code review, privacy standards and more.
2. AI Talent with Compliance Expertise
Our AI engineers are veterans in regulatory compliance surrounding data privacy. What’s more, they get to know your specific company AI ethics to ensure all coding fits within your value framework.
3. Customized AI Development Solutions
Finally, we’re not afraid of having difficult discussions about AI and machine learning ethics. Choose our top TECLA AI development talent to get customized recommendations for integrating responsible AI coding. We’ll help you navigate AI ethical concerns from start to finish during your product lifecycle.
Hire TECLA AI Development Talent
Is AI coding unethical? While there are certainly concerns to address, your business can take a responsible approach. Leverage our best practices to undertake ethical AI development and minimize the risks of AI.
At TECLA, our engineering talent is on the frontlines of creating advanced systems using responsible AI coding practices. As you kick off your next project, explore ethical AI development services with us.
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