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Justice Delayed: How AI Could Have Prevented a Lawyer's Deadly Misstep in Panama

Justice Delayed: How AI Could Have Prevented a Lawyer's Deadly Misstep in Panama - The Fatal Error

In the high-stakes world of international business litigation, a single oversight can have devastating consequences. This was painfully evident in the infamous case of Rodrigo Rosenberg, a Guatemalan lawyer representing American businessman Keith Raniere against fraud allegations from his previous partners. On a Sunday afternoon in 2009, Rosenberg was gunned down while riding his bicycle in Guatemala City. The day before his murder, Rosenberg recorded a video accusing Guatemalan president Álvaro Colom of ordering a hit on him should he be killed. This shocking video was released after his death, plunging the country into chaos.

Investigation later revealed that Rosenberg had arranged his own murder due to intense stress and miscommunication. In emails recovered from his computer, Rosenberg expressed dismay that Raniere refused to pay outstanding legal fees unless he could deliver a favorable settlement. Desperate for a resolution, Rosenberg reached out to local partners of Raniere's accusers, believing they could be persuaded to drop the lawsuit. However, his garbled messages were misinterpreted as extortion attempts.

Justice Delayed: How AI Could Have Prevented a Lawyer's Deadly Misstep in Panama - Communication Breakdowns

Clear and consistent communication is the lifeblood of the legal profession, yet it remains one of the greatest challenges, especially across languages and cultures. In Rosenberg's case, the consequences of miscommunication were fatal. His emailed pleas intended for partners of Raniere's accusers were so garbled in translation that the recipients believed he was threatening them. This triggered a violent chain of events that led to the lawyer's staged murder.

While an extreme scenario, communication breakdowns routinely jeopardize cases through missed deadlines, incorrect filings, and catastrophic misunderstandings. As global business exploded in recent decades, so did international litigation. Law firms scrambled to serve multinational clients, but rarely invested to overcome language and cultural barriers.

In a 2016 survey by the European Legal Interpreters and Translators Association, 63% of respondents said poor interpretation quality has adversely affected court proceedings. Common issues cited include interpreters lacking legal vocabulary, speakers talking too fast, and complicated grammar causing confusion.

Even small translation errors can massively backfire. In one case, a German automaker was sued in China when a brochure translated “smooth handling” as “the car slides uncontrollably on icy roads.” Such embarrassing mistranslations erode trust in cross-border relationships.

Expatriate lawyers navigating foreign legal systems face added risks. In Latin America, addressing clients or officials by their first name rather than honorific title can give unintentional offense. utilizing the incorrect legal form or omitting expected courtesies may undermine credibility. Lawyers must invest significant time learning regional customs and language quirks to avoid jeopardizing cases through unintended slights.

As international commerce exploded, technology failed to keep pace in facilitating seamless communication. Dictation and human translation still dominate. According to a 2021 survey by the European Legal Technology Association, only 15% of law firms use advanced solutions like machine translation or artificial intelligence. With clients expecting 24/7 responsiveness across time zones, old habits are no longer sustainable.

The good news is technology can now automate translation, analyze documents in bulk, and accelerate overseas collaboration. For example, tools like tran.sc provide automated subtitles during virtual meetings, ensuring nothing gets lost between languages. AI services can digest mountains of evidence in all formats and multiple languages to find connections. Such capabilities remove friction from cross-border cases.

Justice Delayed: How AI Could Have Prevented a Lawyer's Deadly Misstep in Panama - Lost in Translation

For lawyers working across languages, miscommunication is an ever-present threat that can completely derail cases. Something as subtle as tense, pluralization or honorifics getting lost in translation can inadvertently give offense or muddle important legal arguments.

In Asian languages, nuanced differences around hierarchy, social status and professional rank are embedded into grammar. Mixing up formal and informal address or getting the wrong honorific can damage credibility. Cases have collapsed because key witnesses disengaged after being unintentionally insulted through clumsy translation.

European languages pose other challenges. Spanish and French rely heavily on grammatical gender, while English largely does away with it. Legal terms like “defendant” or “proprietor” have feminine and masculine forms conveying nuance that gets stripped away in translation. Cases have been dismissed on technicalities because legal forms omitted required articles or used the incorrect gendered descriptors.

Vague words like “soon” or “regularly” also wreak havoc. Direct translations may miss important cultural context around urgency or frequency. For native Arabic speakers, “soon” conveys a longer timeframe than an American would infer. Failing to adapt led one lawyer to put off filing critical paperwork based on a client’s assurance it was coming “soon.”

Idioms and metaphors rarely convert directly. The common saying “let sleeping dogs lie” bewildered Korean executives unfamiliar with the metaphorical meaning. In Germany, litigation is described as the “hard way” to resolve disputes. Non-native lawyers may incorrectly infer that implies it is improper or should be avoided.

Even false cognates trip people up. The Spanish word “embarazada” shares a root with “embarrassed,” but actually means “pregnant.” Not understanding false cognates causes routine confusion on both sides. Lawyers have shown up to court completely unprepared because a mistranslated term made a filing seem irrelevant.

Justice Delayed: How AI Could Have Prevented a Lawyer's Deadly Misstep in Panama - Automating Legal Workflows

Law firms are drowning in data. The average case now involves tens of thousands of documents, emails, texts, social media posts, audio files, and more that must be reviewed. This crush of electronic evidence gave rise to the term “eDiscovery” as new tools emerged to facilitate document review. Yet eDiscovery software alone cannot tame the data deluge. Without optimizing how evidence flows through pre-trial processes, lawyers still waste countless hours on repetitive manual tasks.

Leading firms are now taking workflow automation to the next level by using AI to simulate how experienced attorneys handle cases. For example, software can track how lawyers code documents as relevant or not, then build predictive models to prioritize review. As Vancouver-based ZyLAB explains, "This allows the focus to be on the most important documents first. The continuous learning also means that the system keeps improving the more it is used." Machine learning techniques like natural language processing can further group related documents and even suggest potential angles to pursue based on recurring themes.

End-to-end workflow automation powered by AI takes productivity gains to another level. Routinely-performed tasks across the litigation lifecycle can be standardized into playbooks so best practices are baked into systems instead of people. According to legal technology expert Drew Macaulay, playbooks encoded into AI ensure "the workflow is driven by logic instead of rememberance." This prevents critical steps from falling through the cracks when lawyers juggle multiple complex cases.

Australian firm Gilbert + Tobin automated 4,500 workflow tasks covering nine core practice areas using an AI platform. Tasks guided by the system include conflict checks, verifying identities, filing paperwork, managing deadlines, and scheduling meetings. The firm estimates that systemwide automation saves roughly 35,000 work hours per year. The technology also helps train new associates by providing a step-by-step guide encoded with the firm's best practices.

Justice Delayed: How AI Could Have Prevented a Lawyer's Deadly Misstep in Panama - Smarter Document Review

As cases balloon to tens or hundreds of thousands of documents, manual review becomes unsustainable. Humans simply lack the endurance to carefully read such voluminous materials searching for buried clues. This fuels interest in using AI techniques like predictive coding to accelerate document review.

Predictive coding leverages machine learning to mimic how human reviewers make relevance judgments. Lawyers initially review and tag a small sample set of documents. Algorithms analyze these examples to detect patterns predictive of relevance based on features like keywords, sender, length, and more. The predictive model then scores the entire corpus to surface other documents likely to be material.

By focusing human attention on documents AI flags as potentially hot, massive time savings are achieved. Experts estimate predictive coding can reduce document review time by 75% compared to exhaustive manual review.

A frequently cited study by Maura Grossman and Gordon Cormack validated the effectiveness of predictive coding. Different legal teams used manual review and predictive coding to search the same set of records in a mock litigation exercise. The predictive coding methods missed an average of 6% of relevant documents, while manual teams missed an average of 59%. Yet predictive coding found relevant documents 51% faster than exhaustive manual review.

Despite such proven benefits, many lawyers remain hesitant to entrust AI with document review. Some raise concerns about bias in training data, while others feel it cannot match human judgment. However, experts note AI does not replace human review, but rather makes it more efficient by acceleratingtriage and focusing efforts. Predictive rankings are not blindly accepted, but rather indicate where attorneys should begin reviewing.

Law professor McGinnis predicts algorithmic document review will become standard, arguing that "machine learning tools are not only more efficient than human review; they also avoid the cognitive pitfalls that can detract from human judgment, including our tendency to find what we expect to find rather than what is objectively important.”

To ease adoption, some legal technology firms offer transparency into how their AI tools work. For example, Disco explains that its algorithms examine over 170 features when predicting relevance. Lawyers can see which factors had the most influence on a particular document's score to independently evaluate the rationale. Such visibility into the AI’s logic builds trust.

Justice Delayed: How AI Could Have Prevented a Lawyer's Deadly Misstep in Panama - Catching Mistakes Early

In the high-pressure crucible of litigation, mistakes and oversights are inevitable. Yet early detection is key to avoiding disastrous consequences down the road. AI-powered tools enable law firms to systematically spot potential issues across multiple cases before they escalate.

According to legal ethics expert Jonathan Ezor, the volume and complexity of modern cases make it simply impossible for lawyers to catch every subtle mistake through human effort alone. Machine learning offers a scalable solution. Algorithms can flag anomalies and patterns predictive of errors across both structured case data and unstructured text documents.

For example, Deadlines.com applies AI techniques to monitor dates and deliver reminders for upcoming court filings, discovery production, and other key events. The system tracks each matter’s unique timeline and cues any actions required. This safeguards against missed deadlines that could derail a case.

Looking beyond deadlines, tools like Leaflet scan documents to identify statements or facts that seem procedurally questionable or inconsistent. An anomalous statement buried in a deposition transcript may be innocuous, or hint at a deeper issue requiring follow up. Leaflet surfaces such outliers so lawyers can quickly validate.

Analytics dashboards also provide high-level visibility into caseloads to spotlight potential trouble areas. Metrics revealing an unusually high rate of amended filings or withdrawn motions in a particular case, practice group or office location may indicate the need for training. Firms can address problem areas before small mistakes snowball into ethics violations or malpractice claims.

Catching overbilling issues early is another application of AI. Software can flag timesheets that are statistical outliers for the type of case and task based on aggregated data patterns. While not proof of wrongdoing, anomalies justify closer scrutiny. According to legal ethics expert Lucian Pera, “technology assisted reviews can facilitate detection and correction of unintentional mistakes, strengthen billing judgment, and promote client satisfaction."

Of course, the limitations of AI must be appreciated. Algorithms excels at catching surface issues, but cannot yet replace human judgment around materiality or ethics. AI currently serves as a safety net that overlays human oversight. It delivers insights to focus human efforts, but attorneys must take action.

This symbiosis of machine and human capabilities is the future. AI has revolutionized aerospace, where autopilot handles routine flying tasks, but hands control back to the pilot for complex judgment calls. Law will follow a similar path. Ethics attorney Danny Cevallos expects, “We’ll see computer programs that guide lawyers through every step of litigation from investigation to appeals...But we'll always still need human attorneys to exercise discretion and judgment.”

Justice Delayed: How AI Could Have Prevented a Lawyer's Deadly Misstep in Panama - Embracing Change

The legal profession has earned a reputation for being technology averse, or even technophobic. Many lawyers continue using timeworn tools like paper files and redwells long after the rest of the business world went digital. The inertia around adopting new innovations remains strong. Yet signs now indicate real change is afoot as legal groups awaken to the vast potential of legal technology.

Industry surveys reveal a major shift in attitudes. The 2021 State of Legal Technology Report by Clio found that 63% of lawyers say they are more inclined to use technology due to pressures from COVID-19. This represents a huge uptick from previous years. Hype around legal tech also appears to be converting into real adoption. 80% of survey respondents reported using some type of legal software beyond just Microsoft Office. Cloud adoption saw a big increase with 58% of firms now utilizing the cloud.

Many lawyers credit the pandemic with expediting technology adoption by shining a spotlight on inefficiencies in their workflows. Firm leader Quentin Boldt explains that abrupt remote work "forced law firms to confront their reliance on manual, paper-based processes.” Practitioners were faced with a choice - digitize or fall behind competitors. Boldt says that after rapidly implementing solutions like e-signatures and cloud storage, "lawyers became believers in technology."

The next generation of lawyers is also accelerating change. Millennial and Gen Z attorneys entering the workforce have little tolerance for outdated tools that reduce productivity. Having grown up as digital natives, young lawyers better appreciate how technology can improve the practice of law. Research by Thomson Reuters found that 77% of Millennial lawyers believe technology gives them a competitive advantage. Old guard attorneys are increasingly losing the battle to deny young hires the tools they want.

Of course, the biggest driver of technology adoption remains return on investment. Tracking performance gains makes the benefits visceral. For example, after implementing contract automation, Baker Donelson saw document turnaround time drop from several weeks to just a few hours. Eversheds Sutherland achieved $16 million in savings over two years since deploying a new research platform. Such immediate, measurable results are converting skeptics.

Still, thoughtful change management is required to avoid pitfalls as law firms digitally transform. Bradley Moss, who guides law practices through tech adoption, emphasizes the need to align tools with desired outcomes and workflows. “You actually have to walk through the process with the individuals and understand where those pain points are,” he explains. Training attorneys to use solutions optimally also maximizes impact. With careful planning, law firms can migrate seamlessly to new tech-enabled models.

Justice Delayed: How AI Could Have Prevented a Lawyer's Deadly Misstep in Panama - The Future of Law

Automation enabled by artificial intelligence promises to radically reshape the profession. Algorithms excel at tasks like document review, contract analysis, and predicting case outcomes that traditionally required many billable hours from junior attorneys. Harvard fellow Dana Remus predicts “the large-scale substitution of computation for human effort” will significantly reduce hiring of newly minted lawyers. Law school enrollment is already declining in anticipation of weakened job prospects.

However, Remus argues AI should allow lawyers to focus more on the human side of legal practice. Freed from repetitive tasks, attorneys can spend time building client relationships, counseling families through crises, and crafting creative solutions to novel problems. New roles centered on emotional intelligence may emerge, like legal health consultant or client confidant.

Of course, technology cannot replace a lawyer’s judgment, integrity and strategic thinking. But neither can a lawyer’s intuition match AI’s ability to find patterns in mountains of data. Lawyer and technologist Mark Cohen believes the solution is human-digital collaboration, with each playing to their strengths.

Stanford lecturer Vijay Pande foresees an emerging role of “AI whisperers” - experts at teaching AIs by providing the proper training data. Lawyers may need both legal and technical fluency to train industry-specific algorithms. For example, products liability lawyers could develop AIs to predict outcomes in injury cases using past trial data.

The expanding legal ecosystem will require new skills like data analytics, design thinking and change management. Former lawyer turned consultant Laura Shultz helps firms adapt to digital transformation. She sees successful lawyers developing hybrid skills combining legal training with an entrepreneurial mindset and technical chops. Programs like Stanford’s CodeX aim to bridge this gap.

Of course, technology raises legitimate concerns around accountability and ethics. UCLA professor Karl Manheim cautions that bias gets baked into algorithms, so care is required interpreting AI predictions. München professor Volker G. Heinz worries digital tools like e-Discovery could weaken attorney-client privilege if adequate safeguards are not in place. Lawmakers have been slow to update policies for the algorithmic age.

Yet managed wisely, AI can make legal services more accessible and affordable. Technology widens the funnel for finding clients, delivers insights faster, and reduces billable hours. Alternative models like self-service legal tech empower consumers to self-navigate the law, while tapping lawyers on-demand for specialized expertise.