Responsible Innovation and AI Adoption: 8 Policy Considerations for Employers


Discover Talent Today

Responsible Innovation and AI Adoption: 8 Policy Considerations for Employers

As technological advancements continue to reshape industries, organizations are increasingly turning to artificial intelligence (AI) to enhance their operations. However, AI integration comes with several concerns that cannot be overlooked.

This article explores concerns around the use of AI, the role of AI policy in promoting responsible innovation, and how to develop policies that address the use of AI technology in the workplace.

By delving into these key considerations, employers can navigate the complex landscape surrounding AI implementation, ensuring compliance, fostering trust, and harnessing the full potential of this transformative technology.

Key Ethical Concerns Associated with AI Implementation 

The use of AI has improved daily operations, even allowing smaller companies to thrive despite having limited resources. AI has brought about changes that revolutionized the way our world operates. However, there are still things that organizations and every individual should consider before deep-diving into AI.

Data Collection

AI systems heavily rely on vast amounts of data, including personal and sensitive information. Users may not always be aware of the extent to which these systems collect, analyze, and share their data.

One example is how ChatGPT fails to provide users with adequate notification regarding the data collection and how it lacks a legitimate justification for gathering personal information to facilitate AI training. These can undermine user control over their personal information, leading to privacy breaches.


According to a study conducted by AI researchers at Cornell University, DALL-E-2 predominantly generated white men in 97 percent of the cases when asked to create an image of people in authority.¹ Conversely, GPT states that it may occasionally generate incorrect, harmful, or biased content.

AI algorithms are prone to bias since they extract from historical data that may reflect societal biases. If these biases are not properly addressed, the algorithms can perpetuate and amplify discriminatory practices even in the workplace.

For instance, biased AI systems used in hiring or lending decisions can unintentionally discriminate against certain groups based on race, gender, or socioeconomic status.

What Are the Legal Implications? 

Many jurisdictions have implemented data protection laws that govern personal data collection, storage, processing, and transfer.


  • General Data Protection Regulation (GDPR)
  • California Consumer Privacy Act (CCPA)


Some legal frameworks emphasize the importance of accountability and transparency in AI models. For example, the GDPR includes provisions for individuals’ right to explanation, which requires organizations to provide meaningful descriptions of AI-based decisions that significantly affect individuals.

Similarly, discrimination resulting from biased AI algorithms may be subject to legal consequences under anti-discrimination laws. These laws prohibit unfair treatment based on protected characteristics such as race, gender, age, or disability. Since the use of AI can lead to discriminatory outcomes, it is expected that automated systems should be tested to help ensure it is free from any form of algorithmic discrimination before they can be used.²

8 Best Practices to Develop a Corporate Use Policy for Artificial Intelligence 

Developing AI regulation policies involves careful consideration of various factors to ensure the responsible and ethical use of this technology. Here are some best practices to guide the development of corporate policies:

1. Understand the technology to practice ethical and responsible use.

Begin by thoroughly understanding AI models, their capabilities, limitations, and potential risks. This knowledge will enable you to develop informed policies that address specific concerns associated with AI.

Policies govern the development, deployment, and use of AI, helping to prevent potential harm, bias, discrimination, or privacy breaches. These policies promote accountability and transparency, fostering public trust in AI technologies.

2. Manage risks by defining the purpose and scope.

Identify the specific use cases and applications of generative AI permitted within the organization. Ln doing so, you can set boundaries and provide clarity to employees regarding the acceptable uses of artificial intelligence.

It minimizes potential risks such as data breaches, algorithmic bias, security vulnerabilities, and unintended consequences of AI. By proactively addressing these risks, businesses can implement measures to mitigate them and protect their operations, reputation, and stakeholders.

3. Address data and privacy concerns in compliance with laws and regulations.

AI often relies on large datasets, including personal and sensitive information. Develop guidelines to ensure that data used in AI models comply with relevant privacy laws and regulations. Clearly define the types of data that can be used and establish protocols for data anonymization, access control, and data retention.

An AI policy helps ensure compliance with data protection, privacy, security, anti-discrimination, and intellectual property laws, among others. By establishing clear guidelines, businesses can minimize legal risks and avoid potential penalties or consequences associated with non-compliance.

4. Mitigate bias and discrimination.

While the AI space may contain biases and prejudices due to its nature, there are things you can implement to alleviate these concerns and foster a more inclusive environment in your AI implementation.

Establish guidelines to address bias and discrimination issues in the development and deployment of AI. Implement strategies such as diverse and representative training data, algorithmic audits, and fairness assessments to minimize biases and promote fairness.

5. Establish intellectual property guidelines.

Clarify whether the generated content is subject to intellectual property protection, and define guidelines for its use, licensing, or distribution. Consider the implications of AI application on copyright laws and ensure compliance.

A policy can address issues related to intellectual property rights. They outline ownership and usage rights, licensing agreements, and intellectual property protection strategies for AI development, algorithms, and datasets.

6. Promote transparency and accountability.

Encourage the development of explainable AI models to provide understandable insights into the decision-making process. Establish mechanisms for auditing and validating the outputs of AI models to ensure their integrity and reliability.

Using an AI policy may require businesses to provide understandable explanations of how ai-based decisions are made, especially when these decisions significantly affect individuals. Transparent AI systems enhance user trust, facilitate audits, and enable accountability for the outcomes of AI technologies.

7. Provide training and awareness.

Provide training and awareness programs for employees to understand the principles, guidelines, and policies associated with AI models. Educate them about the ethical considerations, potential risks, and responsible use of AI. Foster a culture of ethical AI use and encourage employees to report any concerns or potential issues.

An AI policy often provides guidelines and training that ensures employees understand their roles and responsibilities, ethical considerations, data protection measures, and best practices for AI system management, promoting a culture of responsible AI use within the organization.

8. Collaborate and foster stakeholder engagement for consistent and standardized operation.

Involve relevant stakeholders, including legal, compliance, IT, and privacy teams, in policy development. Seek input from employees, customers, and other stakeholders affected by the use of AI. You can also consider engaging in dialogue with external experts or organizations to stay informed about emerging trends and best practices.

It helps promote consistency and standardization in ai-related practices across different business units or departments. This ensures that AI technologies are deployed consistently and in alignment with organizational objectives and values by establishing common frameworks for decision-making, development, and implementation of AI models.


Fostering diversity within your workforce brings forth a wealth of fresh ideas, diverse perspectives, and valuable experiences that fuel creativity and innovation.

At Strategic Systems, we firmly believe that everyone is a unique entity and should not be judged based on biases. Our focus lies in identifying and selecting professionals with the necessary skills and qualifications for the job, regardless of their background.

Contact us today to learn more about how we can help!


1. Luccioni, Alexandra, et al. “Stable Bias: Analyzing Societal Representations in Diffusion Models.” Cornell University, 20 Mar. 2023,

2. “Algorithmic Discrimination Protections.” White House Government, 28 Jun. 2023