The Power of AI for Negotiations – The Marcel A. Desautels Centre

Written by: Khaled Abdelwahab

INTRODUCTION

Will AI replace human negotiators? In this blog, we dive into the world of transformational technologies, such as artificial intelligence and machine learning, and explore their impact on the negotiation process. AI affects many professional occupations, such as purchasing managers, lawyers, judges, and their respective industries. Perhaps it is critical to analyze how communication media affects the quality of negotiation outcomes and how technology can assist in this regard. More importantly, we shed some light on how AI can enable human negotiators to achieve mutually beneficial outcomes by focusing on interests rather than positions.

Negotiation and Conflict in the Age of AI

Artificial intelligence (AI) and machine learning (ML) can potentially transform many industries. One exciting area of research is these technologies’ impact on negotiations, whether in businesses or courtrooms. Such technologies can also improve how humans learn to negotiate. These technologies are recently being adopted widely under brands like ChatGPT. The systems are being utilized for educational purposes, where they help human negotiators better understand and digest roleplay simulations. One key distinction of such technologies is that they can personalize negotiation instructions, considering criteria like culture and bias (Dinnar et al., 2021).

Research suggests that technology can enhance the initial negotiation phase to improve the generation of options for mutual gain. For example, Electronic Meeting Systems (EMS) are being augmented with negotiation-specific modules to provide negotiation support systems. However, as technology advances, we need to understand the impact of communication media on negotiation. Soon, negotiation meetings will occur virtually between artificial intelligent systems rather than humans. Virtual negotiations between humans have significantly increased over the past decades due to macro trends like COVID. Communication media set the context for communication, influence communication patterns and affect managerial effectiveness. For example, up to ninety-three percent of the meaning of a message is contained in facial and vocal cues rather than in text (Poole et al., 1992). What would be the impact of human-to-machine negotiation or even machine-to-machine communication between AI systems presenting different entities? Technology virtual reality that aids in improving communication media will make negotiators more likely to collaborate and be present.

To illustrate, purchasing departments use AI to support the complex decision-making process. AI can analyze the predefined rules of an upcoming negotiation and make predictions of the expected outcomes of the suggested negotiation tactics. The system could analyze individual negotiation behavior to predict the supplier’s behavior, analyze cost breakdowns, reduce purchasing costs, and identify price patterns. These prediction capabilities are superior to most human negotiators and will lower the barrier of entry for novice professionals entering the supply chain career (Schulze-Horn et al., 2020). Arguably, any new technology is met with skepticism. The pure act of negotiating prices might be automated by both parties in the long term. This scenario poses a dilemma. How will prices be determined, and will the final quote depend on the effectiveness of the AI technology? Will negotiation robots become so intelligent that they replace supplier and purchaser’s negotiators?

Similar existential dilemmas exist in the legal arena, where there is a growing rise in the number of self-represented litigants. For instance, a study conducted for the American Bar Association in the Supreme Court of Maricopa County, Arizona, USA, indicated that at least one of the parties was self-represented in over 88% of domestic relations cases, and both parties were self-represented in 52% of the cases (Zeleznikow, 2017). The proliferation of large language models like ChatGPT has saved individuals up to 30% in legal bills (Brochner, 2023). As with the internet, which took away work from lawyers when people could find legal information online, AI will likely take away plenty of administrative work. Lawyers will become hyper-augmented, which might turn them to higher-order tasks where they can provide incremental value to the profession by leveraging such technologies rather than considering them a threat. Arguably, the legal industry is among the most vulnerable in the AI movement (Felten et al., 2023). However, the productivity gains will eventually result in improved services for legal consumers. The legal profession may even have to fundamentally change its business model to cope with the change and emerge stronger by adopting new technologies.

Similarly, such technologies may reshape the judging process by replacing or supplementing the judicial role. Humans may find they are less engaged in judging, with an increased emphasis on AI to deal with more minor civil disputes (Tania, 2018). As we have seen with the industrial revolution, machines did not replace factory workers. Instead, they enjoyed productivity gains and enhanced skills.

Researchers have proposed practical models that can help professionals navigate the complex negotiation and conflict resolution process with the aid of technology (Sycara, 1993). Negotiation and conflict resolution are among the major unstructured tasks that need technological advancement. The outcomes of the negotiation process depend on qualities like the negotiators’ skills and experience, perception of information, cognitive biases, and the structured analysis of the problem. Negotiation meetings are quite dynamic and ever-evolving. Therefore, the issues are complex and unstructured and with uncertain outcomes. Consequently, pervasive technologies like artificial intelligence and machine learning are urgently needed. The system can consider, as inputs, the user’s goals, tradeoffs, and BATNA. It can also generate appropriate arguments to help participants focus their attention on interests rather than positions. This capability can aid participants by finding shortcuts to what otherwise would be a lengthy and unproductive negotiation process that includes repeated tasks or mistakes.

CONCLUSION

This discussion aimed to demystify the impact of artificial intelligence and machine learning on negotiations and conflict resolution. Practical implementations show the power of such pervasive language models, like ChatGPT, to produce win-win outcomes and assist integrative negotiation styles. If appropriately used, professionals can harness the power of these systems rather than viewing them as a threat to their occupation. Finally, intelligent systems can help lower the entry barrier into negotiation practices for new professionals by personalizing negotiation instructions, making it easier to learn and navigate conflict resolutions.

References

Brochner, N. (2023, June 22). Will AI Replace Lawyers? Forbes. Retrieved July 29, 2023, from https://www.forbes.com/sites/forbestechcouncil/2023/05/25/will-ai-replace-lawyers/?sh=7cd304fd3124

Dinnar, S., Dede, C., Johnson, E., & Straub, C. (2021). Artificial Intelligence and Technology in Teaching Negotiation. Negotiation Journal.

Felten, E., Raj, M., & Seamans, R. (2023). How will Language Modelers like ChatGPT Affect Occupations and Industries? NYU Stern School of Business.

Poole, M., Shannon, D., & DeSanctis, G. (1992). Communication media and negotiation processes. American Psychological Association.

Purdy, J., & Nye, P. (2000). The Impact of Communication Media on Negotiation Outcomes. The International Journal of Conflict Management, 11, 162-187.

Schulze-Horn, I., Hueren, S., Scheffler, P., & Schiele, H. (2020). Artificial Intelligence in Purchasing: Facilitating Mechanism Design-based Negotiations. Applied Artificial Intelligence.

Sycara, K. (1993). Machine learning for intelligent support of conflict resolution. Decision Support Systems.

Tania, S. (2018). Judge v Robot? Artificial Intelligence and Judicial Decision-Making. University of New South Wales Law Journal, 41(4), 1114–1133.

Zeleznikow, J. (2017). Can Artificial Intelligence And Online Dispute Resolution Enhance Efficiency And Effectiveness In Courts? International Journal For Court Administration.

The views and opinions expressed in the blogs and case reporter are the views of their authors, and do not represent the views of the Desautels Centre for Private Enterprise and the Law, the Faculty of Law, or the University of Manitoba. Academic Members of the University of Manitoba are entitled to academic freedom in the context of a respectful working and learning environment.