Introduction

This issue, which currently preoccupies people, goes back a long way. The evolution of technology, which has been ongoing for at least seven centuries, starting from the introduction of the horse collar in Europe, presents a complex and diverse issue concerning its impact on job replacement, a topic that spans multiple centuries. We have now entered an era dominated by artificial intelligence (AI), which is radically altering many professions. The domain of mediation and neutral conflict resolution is not exempt, as it too experiences the transformative influence of this technology. While AI technology’s integration into various sectors has historically oscillated between replacing and creating jobs, its role in mediation raises unique questions about the balance between human empathy and machine efficiency.

Brief History of How Technology has Impacted Employment

Pre-Industrial Era

• Agricultural Innovations: Before the Industrial Revolution, agricultural innovations like the plow and irrigation systems gradually replaced many manual labor jobs in farming. However, these innovations also led to increased agricultural productivity and eventually supported larger populations.

Industrial Revolution (18th - 19th Century)

• Mechanization of Textile Industry: The introduction of machines in the textile industry in Britain, such as the spinning jenny and the power loom, significantly reduced the need for hand-weaving, impacting artisan jobs.
• Steam Power and Machinery: Steam power led to the development of machines that could perform work faster and more efficiently than human labor, leading to the decline of certain crafts and trades.

20th Century

• Automotive Assembly Line: The introduction of the assembly line by Henry Ford revolutionized manufacturing, increasing productivity but also replacing many skilled labor positions with less skilled, repetitive tasks.
• Computers and Automation: The mid-to-late 20th century saw the rise of computers and automation in various industries, leading to significant changes in the workforce. Many administrative and repetitive jobs were automated, but new jobs in technology and programming emerged.

21st Century and Beyond

• Internet and Information Age: The rise of the internet transformed numerous industries, from retail (e-commerce) to media and entertainment. While it led to the decline of some traditional jobs (like bookstore clerks), it created new opportunities in digital marketing, web development, and data science.
• Artificial Intelligence and Robotics: AI and robotics are currently transforming industries, automating tasks ranging from manufacturing to customer service. While this leads to job displacement in certain sectors, it also creates new opportunities in AI development, data analysis, and tech maintenance.

In the modern industrial age, cost-efficiency and productivity are key drivers of profitability. Many medium and large-scale businesses have ventured into AI and robotics to ramp up sales while lessening staffing costs. The latest stats on the Robotics Industry show that by 2030, 90% of businesses plan to embrace robotic automation into their infrastructure, which might seem alarming for the human side of employment.

• By 2030, 375 million jobs worldwide will be at risk.
• 14 to 80 million US jobs are at risk of being automated.
• Automation is predicted to displace 20 million manufacturing jobs by 2030

In the modern industrial age, cost-efficiency and productivity are key drivers of profitability. Many medium and large-scale businesses have ventured into AI and robotics to ramp up sales while lessening staffing costs. The latest stats on the Robotics Industry show that by 2030, 90% of businesses plan to embrace robotic automation into their infrastructure, which might seem alarming for the human side of employment.

(forbes)

The Nature of Mediation and Neutral Work.

Mediation and neutral work, in many cases, rely on human attributes such as empathy, emotional intelligence, and the ability to navigate complex social dynamics. These skills are crucial in understanding the subtleties of conflict and facilitating resolutions that are acceptable to all parties involved. However, we now live in a world of interruptions, information overload, misinformation, too many false choices, biases and especially mobile phone and social media addiction. The use of social media has left us particularly vulnerable to confirmation bias, or the propensity to fix upon evidence that shores up our prior beliefs. The question arises: can AI, with its current capabilities, mitigate the bad effects of social media influence and replace the inherently human skills needed for successful mediation?

AI in Conflict Resolution: A Historical Perspective

Historically, technological advancements have both displaced and created jobs. The industrial revolution, for instance, replaced many manual jobs but created new opportunities in factories and industries. In the realm of AI, we see a similar pattern. AI has replaced some jobs, particularly those involving repetitive tasks, but has also created new roles, such as AI trainers and ethicists. In mediation, AI's role has been more about transformation than replacement. Tools like predictive analytics and automated negotiation algorithms like SmartSettle One, Negobot, Modria, etc. have assisted mediators, particularly in collaborative negotiation, rather than replacing them. Another example is NextLevel™ Mediation. It was one of the first mediation platforms to use AI in combination with Decision Sciences tools to assist and augment the skills of the mediator. Rather than replace the mediator, the AI assisted tools helped the mediator generate and analyze questionnaires, understand disputing party priorities, and suggest potential areas for negotiation.

Current Flaws and Limitations of AI in Mediation

Despite its advancements, AI in mediation faces significant challenges. One of the primary limitations is its inability to fully understand and interpret human emotions and cultural nuances. AI systems are also only as good as the data they are trained on, which can lead to biased outcomes if the data is not diverse and comprehensive. Furthermore, AI's decision-making processes (recognizing patterns and correlation) can be opaque, leading to trust and credibility issues. Given the non-deterministic nature of Large Language Models, Mediators must also be the human in the loop to protect against:

• Hallucinations: In artificial intelligence (AI), a hallucination or artificial hallucination (also called confabulation or delusion) is a confident response by an AI that does not seem to be justified by its training data. Hallucination can occur when the AI model generates output that is not supported by any known facts. This can happen due to errors or inadequacies in the training data or biases in the model itself.
• Biases: Biases can occur when there are errors or inadequacies in the training data or biases in the model itself. For example, if a Large Language Model was trained on biased data, it may produce biased output.
• Inability to think outside the box: A big disadvantage of AI is that it cannot learn to think outside the box. AI is capable of learning over time with pre-fed data and past experiences but cannot be creative in its approach.
• Transparency: AI decisions are not always understandable to humans

Legal and Ethical Considerations

The integration of AI in mediation also brings legal and ethical considerations to the forefront. Questions about accountability, especially in cases of flawed AI-mediated decisions, are paramount. The legal framework governing AI's role in mediation is still in its nascent stages, requiring careful consideration of issues like data privacy, consent, and liability. Although there is a beginning worldwide effort to regulate AI, we are far from having an agreed upon framework. Different nations harbor varied perspectives on the deployment and control of AI technologies, influenced by their unique socio-political and economic contexts. While some countries advocate for stringent regulations to mitigate potential misuse and uphold ethical standards, others pursue a laissez-faire approach, fostering innovation and development at the risk of potential ethical transgressions.

Addressing these ethical considerations requires a collaborative effort among AI developers, mediators, ethicists, and legal professionals. The development and implementation of AI in mediation should be guided by ethical frameworks and standards that prioritize fairness, transparency, and respect for human dignity.

AI Assisting, Augmenting and Transforming Mediation Jobs

Rather than outright replacement, a more likely scenario is AI transforming the role of mediators. AI and decision analytics can handle certain tasks like preliminary data gathering, analyzing documents, understanding priorities, identifying areas for negotiation, or drafting initial settlement proposals. This integration allows human mediators to focus on more complex aspects of the mediation process, such as understanding emotional undercurrents and building trust among parties.

Conclusion

In conclusion, while AI brings efficiency and a data-driven approach to mediation, it is not poised to replace human mediators entirely. The current limitations of AI in understanding the full spectrum of human emotions and cultural contexts, coupled with legal and ethical concerns, suggest a future where AI acts more as an assistant than a replacement. The evolution of AI in mediation is likely to follow the historical pattern of technology reshaping rather than eradicating jobs, leading to a transformed landscape where human mediators leverage AI for enhanced effectiveness and reach. As this field evolves, continuous evaluation and adaptation will be crucial in ensuring that integrating AI in mediation serves to augment, rather than undermine, the human element that is so vital to conflict resolution.