At this point, we must acknowledge: AI is not going anywhere, and if anything, there is a growing expectation that it will be built into critical business functions. Now is the time to set the stage for ethical AI, leveraging the advantages of cutting-edge technology while also intentionally establishing guardrails. These ethical guidelines are especially crucial in strategic communication, which, even without AI in the picture, would encompass a range of complex ethical concerns. These are worth addressing because, if not approached strategically, AI can diminish trust and credibility — the core objectives associated with strategic communication.
Below, we reveal how AI and ethics can come together to support strategic communication as well as how a strategic communication master's degree can elevate this effort. Our goal is to clarify: What is AI ethics, and why does it matter?
Since then, AI has reshaped all aspects of the digital experience, from journalism and education to finance and even hospitality. Advocates regard AI as a powerful tool capable of enhancing efficiency and strategic decision-making. However, skeptics worry about the ethical implications of AI. Criticisms surround low-quality content such as “AI slop,” for example, along with inaccuracies that can place individual consumers and entire businesses or industries at risk.
AI ethics can address these challenges, recognizing that AI will inevitably continue to play a prominent role in the industries and innovations of tomorrow — and that, as this technology continues to advance, current moral quandaries will become even more significant. SAP defines AI ethics as the many "principles that govern AI's behavior in terms of human values," adding that these moral frameworks shape the use of AI in a way that promotes qualities such as "fairness, transparency, accountability, privacy, [and] security."
Often difficult to identify or avoid, these biases can contribute greatly to discriminatory behavior that impacts job applications, credit decisions, or even treatment planning in the healthcare sector. This may also drive an overarching erosion of trust, causing the public to lose faith in both AI algorithms and the individuals and organizations that use them.
Below, we reveal how AI and ethics can come together to support strategic communication as well as how a strategic communication master's degree can elevate this effort. Our goal is to clarify: What is AI ethics, and why does it matter?
The Rise of AI and Why Ethics Matter
The concept of artificial intelligence is far from new. Largely credited to Alan Turing and his Turing machine, this technology was already utilized heavily as of the 20th century in everything from checkers programs to chemical-analysis expert systems. This technology took another step into the spotlight in 2022, prompting both excitement and widespread criticism with the release of generative AI chatbots such as ChatGPT.Since then, AI has reshaped all aspects of the digital experience, from journalism and education to finance and even hospitality. Advocates regard AI as a powerful tool capable of enhancing efficiency and strategic decision-making. However, skeptics worry about the ethical implications of AI. Criticisms surround low-quality content such as “AI slop,” for example, along with inaccuracies that can place individual consumers and entire businesses or industries at risk.
AI ethics can address these challenges, recognizing that AI will inevitably continue to play a prominent role in the industries and innovations of tomorrow — and that, as this technology continues to advance, current moral quandaries will become even more significant. SAP defines AI ethics as the many "principles that govern AI's behavior in terms of human values," adding that these moral frameworks shape the use of AI in a way that promotes qualities such as "fairness, transparency, accountability, privacy, [and] security."
Identifying the Ethical Concerns of AI in Communication
AI holds great promise for automating mundane tasks and sparking innovation, but its advantages are offset by alarming ethical implications that span numerous industries and already have a documented impact on real-world individuals and enterprises. Understanding these ethical issues can provide a critical first step toward using AI responsibly.Bias, Fairness and Discrimination
Human biases have a way of infusing AI systems. Experts at the National Education Association (NEA) suggest that biases are inherently built into many advanced algorithms. Researchers at the National Institute of Standards and Technology (NIST) add that these biases are fueled by not only the data used to train AI software but also the "broader societal factors that influence how technology is developed."Often difficult to identify or avoid, these biases can contribute greatly to discriminatory behavior that impacts job applications, credit decisions, or even treatment planning in the healthcare sector. This may also drive an overarching erosion of trust, causing the public to lose faith in both AI algorithms and the individuals and organizations that use them.
Understanding Algorithmic Bias
Algorithmic bias occurs when bias occurs directly within computer systems. These prejudiced decisions result from critical errors that exist within the data on which algorithms are trained. This may also result from historical biases that may emerge within vast datasets. As the National Library of Medicine points out, although the impact can contribute to discriminatory decision-making, "Bias doesn’t always mean someone did something wrong or prejudiced." This subtlety, though, makes algorithmic bias uniquely difficult to combat.Examples of Biased Communication Outputs
In strategic communication, AI-driven bias can take various forms. Representation bias is one of the most common concerns, reflecting a lack of diversity in training data or limited diversity among the humans involved in developing and deploying these systems. This can have a dramatic impact; for instance, a lack of diversity in training sets for facial recognition technology could lead to significant inaccuracies when identifying individuals with darker skin. Similarly, AI has been shown to amplify gender bias via male-coded language, which may place women at a disadvantage in hiring and recruitment.Why Fairness Matters in Strategic Communication
Today's strategic communicators hold great power to shape public perception and inspire action. This power can be augmented by advanced AI systems, which draw upon audience analyses while delivering personalization at scale. Fairness must be a core element of this effort, however, reflecting the overarching prioritization of ethics in strategic communication at large. Strategic communicators must understand that their messaging has a marked impact on the lives of their audiences and can even have ripple effects at the societal level. AI can amplify the changes brought about through strategic communication — often in ways that are difficult to predict — so strategic communicators have a fundamental responsibility to use AI with the utmost care.Mitigating Bias in Practice
Diverse data sets are crucial, as algorithms rely on this data to find patterns and to make decisions. Limited representation produces skewed outcomes that may fail to take crucial insights or perspectives into account, thereby promoting inaccurate or outright harmful decisions. Experts at the World Economic Forum recommend diversity within development teams, too, as this helps address far-reaching stakeholder expectations and can also "bring different experiences and perspectives to the table."Transparency and Accountability
AI transparency fosters trust and accountability, ensuring that people understand not only when AI is used but also how it works and why AI models arrive at specific decisions. This, in turn, can increase confidence in AI solutions, confirming that they align with organizational (and deeply human) values.Understanding the "Black Box" Problem
Users struggle to understand how AI systems navigate decision-making processes, especially when advanced models such as deep learning are involved. Inputs and outputs may be readily available to users, but what happens in between often feels downright mysterious. Large language models such as ChatGPT qualify as black box AI, and as experts at IBM point out, "Even their own creators do not fully understand how they work."Importance of Explaining AI Decisions
While the black box problem can be difficult to overcome, strategic communicators can still foster transparency by explaining when AI is used and why. Through ethical AI, communicators can disclose the tools and algorithms that underscore AI-generated content, along with the potential deficits that could accompany this approach. This helps ensure that AI solutions are held to high standards and appropriately scrutinized when they fail to uphold key ethical principles.The Ethical Obligation to Disclose AI Usage
Surveys surrounding public perceptions of AI-generated content indicate overwhelmingly neutral sentiments. These perceptions can be influenced by disclosures surrounding the use of generative or augmented AI. Interestingly, researchers find that users perceive higher quality when viewing content created by human experts — yet, "Knowing that AI is involved in the creation process does not affect its perceived quality." That being said, the need for disclosures extends beyond desires to enhance credibility; this effort also holds great intrinsic value. If audiences are aware of AI's influence, they feel empowered to evaluate content accordingly.Strategies to Ensure Accountability
Transparency-focused frameworks can guide consistency in AI disclosures so that these always accompany AI-generated or AI-assisted messaging. Organizations should perform regular content reviews or AI audits to verify adherence to strict ethical standards. Additional accountability protocols can promote detailed documentation of AI usage while also clarifying oversight responsibilities.Privacy and Data Rights
AI systems collect a wealth of sensitive data but often fail to disclose how this information is used or obtained. This lack of transparency accompanies overarching concerns regarding data privacy, which determines how personal information is used and safeguarded when developing AI systems. This represents one of the public's greatest concerns surrounding AI. For example, a survey from the International Association of Privacy Professionals (IAPP) indicates that 68% of global consumers are "somewhat or very concerned about their privacy online," with 57% agreeing that "AI poses a significant threat to their privacy."AI’s Dependence on Large-Scale Data
The vast data sets discussed above can limit the potential for bias, but these may introduce an entirely different ethical risk: the increased likelihood of compromising user privacy, along with a greater susceptibility in the event of a data breach. To achieve true breadth of data, after all, organizations must constantly push for more information, gathered via purchasing history or social media behavior. As more data points are added, re-identification becomes more likely, even when data appears to be anonymized.Real-World Risks
Data privacy has long been a top source of concern among internet users, but the scope of that data — and the ease of its collection — have evolved greatly. The compromised use of information has grown increasingly dangerous among individuals and even at a societal level. Examples abound, revealing that data privacy issues can have far-reaching impacts. Among creatives, for instance, this can manifest in stolen intellectual property, while poorly safeguarded facial recognition or location tracking systems can contribute to unwanted surveillance.Legal Frameworks and Ethical Considerations
Emerging legal frameworks grant consumers greater control over the collection and use of their personal information. They provide the chance to opt out while also sparking greater awareness over the influence of AI on everyday digital endeavors. Arguably the most influential? The transformative GDPR (General Data Protection Regulation), which establishes strict standards for ensuring informed consent within the European Union (EU). The California Consumer Privacy Act (CCPA) shares many similarities, allowing California residents to opt out from having their personal data sold or distributed.Best Practices for Data Privacy
AI data privacy best practices largely echo privacy initiatives already widely utilized in other aspects of data management. For example, encryption and access controls lay the groundwork for the safe and secure use of sensitive information. Also important is data minimization, in which only strictly necessary data is collected for strategic purposes. Personally identifiable information should be avoided in training sets, with anonymization using generalizations to further protect personal information.Deepfakes and Misinformation
Rampant inaccuracies bring doubt to AI-generated content, which is prone to errors and therefore calls for in-depth fact-checking. Among the numerous concerns regarding the proliferation of AI: deepfakes and misinformation that, although sometimes using different means of deception, are both antithetical to the foundational principles of trust and fairness.What Are Deepfakes? (And Why They Matter)
Artificially generated videos and photos known as deepfakes mimic human facial features and voices to deceive users and spread misinformation. Because these look increasingly realistic, they are capable of skewing perceptions and influencing everything from financial crimes to political campaigns. These are among the most alarming ethical problems with AI because they are so difficult to combat and can have such a profound impact across the full scope of the digital landscape.Risks to Trust and Reputation
AI-produced misrepresentations can quickly compromise strategic communications, polluting the targeted messaging that communicators work so hard to craft. This can have a dramatic effect on organizational reputation by misleading shareholders and the public. Even when organizations are not specifically targeted by deepfakes, their increased presence proves damaging simply because it erodes consumer trust.Ethical Communication Imperatives
A proactive approach can help strategic communicators quickly identify and address deepfakes while also clearly distinguishing their messaging from that produced via deceptive sources. This begins with transparency and a clear commitment to avoiding misleading AI-assisted content. Lax standards can muddy the waters, making it more difficult to distinguish between deepfakes and authorized or authentic content.Proactive Safeguards
As deepfakes continue to grow more sophisticated, they require a more tech-forward approach to identification and mitigation. Deepfake detection tools help by uncovering embedded details within images or videos, which make it easier to verify content authenticity. These tools can pinpoint identifiers known as digital fingerprints and may also highlight color patterns or other subtle signs of alteration.Engaging in Ethical Strategic Communication Using AI
Despite the ethical concerns highlighted above, AI continues to hold great promise in strategic communication, offering expanded insight into audience needs and preferences while enhancing efforts to personalize content. Ethical guardrails deliver the best of both worlds: the chance to leverage AI without deceiving audiences or placing users at risk.Building Ethical Frameworks for AI Use
Drawing on guiding principles such as transparency, accountability, and inclusivity, ethical frameworks provide a roadmap to guide the responsible use of AI in strategic communication. Although guided by ethical principles, these frameworks should be crafted to reflect organizational objectives and use cases, along with identified risks. These guidelines should cover diverse concerns such as data governance, AI disclosures, and human oversight.Responsible Creation and Attribution
Attribution involves the clear acknowledgment of information sources. This has long been a strategic communications best practice, but it may look a bit different in an age of AI. Moving forward, attributions will detail when and how AI models contribute to content. Emerging tools can guide this effort, facilitating attribution statements that detail the use of AI. A promising IBM attribution toolkit highlights the extent of AI's involvement, along with the nature of those contributions (e.g., stylistic versus content edits).Guardrails on Bias and Harm
Built-in bias represents an ongoing (and frustratingly stubborn) element of modern AI solutions, reflecting limited diversity within both data sets and the teams tasked with developing AI solutions. Many teams look to guiding principles known as FAIR (findability, accessibility, interoperability, and reusability) to promote data accuracy, but these don't necessarily guarantee diversity in those data sets. However, in its seven key requirements, the European Commission’s High-Level Expert Group on AI emphasizes "diversity, non-discrimination, and fairness," calling for training data to reflect the diversity of the audiences it will ultimately impact. These and other resources can provide robust guidance to help organizations develop effective guardrails.Maintaining Human Oversight
EU guidance reveals the need for strict human oversight to limit risks to health, safety, or violations of users' rights, especially "when a high-risk AI system is used in accordance with its intended purpose or under conditions of reasonably foreseeable misuse." This oversight could take the form of human-in-the-loop (HITL), in which humans are actively involved in training or decision-making processes. Meanwhile, human-on-the-loop (HOTL) calls for expanded human interaction. Human-in-command (HIC) grants humans the ultimate authority over AI systems.Crisis Preparedness for AI Misuse
AI misuse is not a matter of if, but when. Despite proactive efforts to safeguard users, limit bias, and address deepfakes, the sheer scope of AI lends a certain inevitability to tech-driven crises, including everything from malicious activity to in-house ethical failures. AI can actually be built into this effort, though, as noted by Reputation Architects Inc. founder Jon Goldberg in a piece for the Public Relations Society of America (PRSA). Goldberg suggests that AI tools can accelerate responses, with strategic communicators drawing on intelligent systems to "simulate how [crises] could unfold" while "adapt[ing] communications in real time." This may involve risk dashboards that identify early signs of trouble, along with AI-powered sentiment analysis to determine whether crisis communications actually resonate.Measuring Ethical Impact
AI ethics can and should be quantified to determine whether relevant standards, frameworks, or guardrails achieve their desired impact. Bias detection rates, for example, can uncover imbalances in data sets, while user trust evaluations can reveal whether the use of AI contributes to the long-term erosion of trust. Strict monitoring should also verify compliance with a range of regulations and industry standards.Ethical Practices to Start Today
Familiarizing yourself with AI solutions is key. This may entail delving into the technical side of AI so you understand how exactly content is generated and where ethical missteps are most likely to occur. Begin by exploring resources such as Adobe Firefly or getting involved in open-source communities, such as Hugging Face, that promote collaboration. Keep up with industry authorities such as the IEEE (Institute of Electrical and Electronics Engineers) — especially initiatives such as the AI Coalition. As you build AI into projects, begin exploring mechanisms to promote transparency while also experimenting with bias audits. You can even gain practical exposure to AI ethics via volunteer opportunities involving public relations or civic tech labs.How a Strategic Communications Degree Prepares You for Ethics in AI
As you learn more about the expanding role of AI, consider pursuing a Professional Master of Arts (MA) in Strategic Communication. This degree program introduces you to the power of persuasion and discuss the various tools and techniques that shape public opinion — ultimately empowering you to craft messages that advance organizational goals. Because it emphasizes both communication ethics and cutting-edge tools and technologies, this program helps you learn how to integrate these essentials while leveraging AI.Ethical Theory and Professional Codes
Covering both the legal and ethical components of strategic communication, media ethics coursework delves into the many professional standards that can shape the use of AI and data-driven solutions in strategic communication. This is a great opportunity to familiarize yourself with the Society of Professional Journalists Code of Ethics and the Public Relations Society of America Code of Ethics, especially in the context of advancing technologies.Technology and AI Literacy
The AI Literacy Framework (AILit) reveals the distinct mix of knowledge and competency that promotes responsible and effective engagement with AI solutions. This extends beyond a sheer technical understanding of AI algorithms to encompass practical application, which is promoted via experiential coursework in the strategic communication program. Case studies and projects show how advanced strategic communication theories and technologies play out in digital media environments.Risk Assessment and Crisis Management Skills
As communication crises (especially deepfakes) grow more common, the importance of risk assessment within the strategic communication field grows along with it. To that end, strategic communication coursework explores risk and crisis management in the context of strategic communication leadership and crisis communication. Coursework uses practical exercises and realistic simulations to help students gain confidence in navigating complex crisis scenarios.Capstone and Practicum Integration
In addition to drawing heavily on simulations and projects, the strategic communication master's degree promotes concept mastery and real-world application through a challenging yet compelling capstone experience — involving the creation of a communications plan that reflects present-day organizational challenges. Through this capstone-based execution of a strategic campaign, you gain valuable practice applying ethical frameworks, possibly even getting the chance to responsibly integrate advanced AI tools or techniques along the way.Embrace Digital Opportunities with a Strategic Communications Degree
Prepare for the future of strategic communication with a degree program that balances persuasive techniques with data-driven solutions and ethical understanding. The Professional Master of Arts in Strategic Communication encourages you to step into the future of strategic leadership with confidence. Offered through the University of Minnesota (UMN) Hubbard School of Journalism and Mass Communication, this program is an ideal fit for working professionals with a desire to blend digital transformation with compelling messages. Connect with our team to learn more or complete your online application today.