Harder, Better, Faster… Funded? | Emanuele Rumi Rios | TEDxLink Campus University

Key Concepts

• Legaltech: Tools and solutions based on algorithms and artificial intelligence that assist in performing human activities in the legal sector.
• AI (Artificial Intelligence): Technology that enables machines to perform tasks that typically require human intelligence.
• Predictive Analysis: Using data to forecast future outcomes, applied in legaltech to predict case results.
• Natural Language Processing (NLP): A branch of AI that allows computers to understand, interpret, and generate human language.
• Black Box Problem: The opacity of complex AI systems, where the output is clear but the internal reasoning process is not.
• Bias: Prejudices or systematic errors in data or algorithms that can lead to unfair or inaccurate outcomes.
• Common Law: A legal system where judicial decisions are a primary source of law, with precedents being highly influential.
• Human Judgment: The essential role of human intuition, empathy, and ethical reasoning in legal decision-making.

The Revolution of the Legal Ecosystem: Harder, Better, Faster, Funded

This presentation explores the profound impact of significant capital investment on the legal ecosystem, transforming how legal professionals operate. The speaker, Emanuele Rumirios, an attorney specializing in corporate and commercial law within the technology and creative industries, draws a parallel to the iconic musical duo Daft Punk, whose fusion of man and machine in their music and performances serves as a metaphor for this legal revolution.

The Daft Punk Analogy and Personal Journey

Rumirios begins with a personal anecdote, highlighting his upbringing in a family of successful musicians and tech entrepreneurs. His own aspiration to become a corporate lawyer, while surrounded by synthesizers and samplers, created a unique perspective. A pivotal moment was witnessing a Daft Punk concert at age 16, which he describes as a "perfect, perhaps futuristic, synthesis of machine and man." This experience deeply influenced his career, leading him to specialize in legal tech and creative industries. He reinterprets Daft Punk's hit "Harder, Better, Faster" to "Harder, Better, Faster, Funded," emphasizing the influx of capital as the driving force behind the legal sector's transformation. He promises to explain how Daft Punk's work was prophetic for the legal field.

The Rise of Legaltech: From Cartoons to Reality

The presentation paints a vivid picture of the future of law, imagining courtrooms with AI judges or holographic legal assistants like "Wally" from Pixar. These seemingly futuristic scenarios are not far from the reality being shaped by legaltech startups.

• Definition of Legaltech: Legaltech encompasses tools and solutions powered by algorithms and AI that assist in performing tasks traditionally done by humans in the legal sector. Examples include automated legal research and AI-assisted contract review.
• Market Growth: The traditional legal sector is already a massive market, valued at $1.5 trillion in 2024. However, legaltech is experiencing explosive growth.
  • 2025 Projection: The legaltech market is estimated to reach $29 billion.
  • 10-Year Projection: This figure is projected to grow to $65 billion within a decade, representing a fivefold increase.
• Investment Landscape: This growth is fueled by founders and investors who recognize the business opportunity in making the legal ecosystem "harder, better, faster, and funded."

Case Studies: Exemplifying Legaltech Innovation

Two prominent legaltech startups are presented to illustrate the sector's potential:

1. Lex Machina:

   • Origin: Started as a project at Stanford University.
   • Functionality: Engages in predictive analysis by collecting and analyzing case documents, court proceedings, and judicial decisions across various jurisdictions and subject matters.
   • Purpose: To assist legal professionals in anticipating the likely outcome of a case before a specific judge in a particular court.
   • Analogy: Similar to how Spotify uses listening history to recommend new music, Lex Machina uses past judicial behavior to inform legal strategy.
   • Success: Received millions in early investment and was acquired by a corporation for $175 million.

2. Harvey:

   • Inspiration: Named after the fictional character Harvey Specter from the TV show "Suits," embodying a sharp, intelligent, and effective lawyer.
   • Functionality: Acts as an AI co-pilot or assistant that uses natural language processing to answer complex legal questions and perform tasks.
   • Examples:
     • "What is the difference between an independent contractor and an employee under Italian law?"
     • Identifying clauses in a contract vulnerable to invalidity or nullity challenges.
     • Drafting improved contract clauses.
   • Efficiency: Tasks that previously took days for junior associates can now be completed in 20 minutes or less.
   • Investment and Valuation:
     • Received $5 million from OpenAI's fund.
     • Secured an additional $100 million from Google Ventures.
     • Current valuation: $1.5 billion, making it a legaltech "unicorn" (a company valued over $1 billion).

Critical Challenges and Limitations of Legaltech

Despite the impressive advancements, Rumirios highlights significant critical issues:

• The Black Box Problem:

  • Opacity: Advanced AI systems, particularly deep learning models, can be opaque. While the output is clear, the logical reasoning and intuitive steps leading to the decision are not.
  • Jurist's Role: The core of legal practice involves motivating decisions, explaining reasoning, and guiding listeners through a logical process.
  • Trust Deficit: It is challenging to rely on an AI that provides advice without explaining its rationale.

• Bias and Data Limitations:

  • Data Dependency: Legaltech relies heavily on historical data, which represents a snapshot of past events and may not reflect current realities or evolving legal landscapes.
  • Outdated or Incorrect Data: If the input data is flawed or obsolete, the AI's output will be equally inaccurate.
  • Risk of Dogma: Bias, or prejudice, can reinforce existing inequalities. In common law systems, where precedent is binding, biased data could lead to the perpetuation of flawed legal principles without the possibility of necessary course correction.

The Indispensable Role of Human Judgment

Rumirios uses a scene from Star Wars where Luke Skywalker removes his targeting computer and relies on the Force and his intuition to destroy the Death Star as a metaphor. This signifies that while legaltech tools are invaluable opportunities, they should not be blindly trusted.

• Humanity in Law: The legal phenomenon is fundamentally human, driven by sensitivity, personal intuition, and ethical considerations, as encapsulated by Daft Punk's song "Human After All."
• Exclusive Human Domains: Algorithms cannot replicate human empathy, the understanding of nuanced sensitivities, or the comprehension of responsibility.
  • An algorithm cannot grasp the weight of a signature on a contract.
  • It cannot fully comprehend the impact of initiating judicial proceedings.
  • It cannot truly assess the ramifications for a person's reputation or a business's vision.

Conclusion: A Stronger, Human-Centric Legal Future

The influx of capital ("funded") is making the legal ecosystem "harder" and "better." Legaltech can certainly make processes "faster" when appropriate. However, the ultimate strength of the legal system lies in "stronger" human judgment. The legal ecosystem, empowered by investment and augmented by technology, can become fantastic, but it must remain grounded in human values, empathy, and responsibility.