CaseMark’s Blitz Strategy
CaseMark’s internal approach to building momentum and collaboration across departments.
Ethical AI for unfiltered case analysis: how lawyers can use CaseMark to process sensitive and explicit criminal evidence.
Harvey Weinstein. Jeffrey Epstein. R.Kelly. Jerry Sandusky. Larry Nassar. The sheer volume of explicit evidence in these high-profile cases is staggering. And unlike movies, legal documents don't come with trigger warnings or adult content ratings.
For lawyers, confronting graphic content is a professional necessity, albeit a challenging one. Understanding how this sensitive material might impact a jury is crucial for crafting a winning strategy.
As AI tools become increasingly integral to trial preparation, it's essential to recognize their limitations. Large language models (LLMs) employ safety filters to prevent the processing of harmful content, such as child sexual abuse or hate speech. However, even seemingly straightforward personal injury cases can involve sensitive topics, like "loss of consortium," that may be blocked depending on the explicitness of the testimony.
Consider a prosecutor relying solely on AI-generated summaries for a hate crime or assault case. If the AI filters block relevant content and no human review takes place, the risk of wrongful conviction becomes a serious concern.
PECK-LAW used CaseMark to win a $20 million jury verdict in favor of an African-American woman against her employer, Stanford Health Care, for race discrimination, race harassment, and retaliation. The hate speech cited in this case would normally be blocked by large language models.
CaseMark is specifically designed for litigation. What sets us apart is our ability to process and summarize sensitive materials without the content filters that typically limit AI solutions. This capability is crucial for legal professionals who need to handle cases involving hate crimes, violence, sexual abuse, and other sensitive topics.
Removing sensitive content filters
By default, large language models (LLMs) have highly developed safety measures to mitigate risks such as hate and bias, sexual content, violence, self-harm, etc. But these “adult content” safety measures aren’t helpful to a lawyer trying to thoroughly understand a case, if important content is omitted or altered.
As a company integrating LLM models, CaseMark thoroughly assessed which LLMs to use. We considered whether to use safety filtering and guardrails, and looked into how they impact model safety. We sought to minimize the risk of non-compliance with relevant regulations and laws, while ensuring that our product still achieves its goal of accurate summarization..
What we found was that to effectively summarize material around sexual assault, hate crimes or other sensitive material, we needed unrestricted content filtering. Getting this level of access requires going directly to the LLMs to remove this safety filter. That’s how we are able to offer:
CaseMark's approach to AI represents a careful balance between technological advancement and ethical considerations. By removing certain AI safety filters for specific legal use cases, CaseMark enables legal professionals to access the information they need while still maintaining strict controls on who can use the system. This targeted approach ensures that sensitive content is handled responsibly and only by those with the appropriate clearance and need.
Legal professionals should always review case material. CaseMark helps reduce the burden of repeated manual review, enabling legal professionals to put their focus and energy on the most critical aspects of their cases.
As we continue to navigate the complexities of the digital age, tools like CaseMark demonstrate how AI can be harnessed for good, particularly in litigation. By embracing these ethical AI solutions, legal professionals can work more effectively and ultimately provide better service to their clients and the cause of justice.
The future of litigation support is here, and it's powered by ethical AI.
Ethical AI for unfiltered case analysis: how lawyers can use CaseMark to process sensitive and explicit criminal evidence.
Harvey Weinstein. Jeffrey Epstein. R.Kelly. Jerry Sandusky. Larry Nassar. The sheer volume of explicit evidence in these high-profile cases is staggering. And unlike movies, legal documents don't come with trigger warnings or adult content ratings.
For lawyers, confronting graphic content is a professional necessity, albeit a challenging one. Understanding how this sensitive material might impact a jury is crucial for crafting a winning strategy.
As AI tools become increasingly integral to trial preparation, it's essential to recognize their limitations. Large language models (LLMs) employ safety filters to prevent the processing of harmful content, such as child sexual abuse or hate speech. However, even seemingly straightforward personal injury cases can involve sensitive topics, like "loss of consortium," that may be blocked depending on the explicitness of the testimony.
Consider a prosecutor relying solely on AI-generated summaries for a hate crime or assault case. If the AI filters block relevant content and no human review takes place, the risk of wrongful conviction becomes a serious concern.
PECK-LAW used CaseMark to win a $20 million jury verdict in favor of an African-American woman against her employer, Stanford Health Care, for race discrimination, race harassment, and retaliation. The hate speech cited in this case would normally be blocked by large language models.
CaseMark is specifically designed for litigation. What sets us apart is our ability to process and summarize sensitive materials without the content filters that typically limit AI solutions. This capability is crucial for legal professionals who need to handle cases involving hate crimes, violence, sexual abuse, and other sensitive topics.
Removing sensitive content filters
By default, large language models (LLMs) have highly developed safety measures to mitigate risks such as hate and bias, sexual content, violence, self-harm, etc. But these “adult content” safety measures aren’t helpful to a lawyer trying to thoroughly understand a case, if important content is omitted or altered.
As a company integrating LLM models, CaseMark thoroughly assessed which LLMs to use. We considered whether to use safety filtering and guardrails, and looked into how they impact model safety. We sought to minimize the risk of non-compliance with relevant regulations and laws, while ensuring that our product still achieves its goal of accurate summarization..
What we found was that to effectively summarize material around sexual assault, hate crimes or other sensitive material, we needed unrestricted content filtering. Getting this level of access requires going directly to the LLMs to remove this safety filter. That’s how we are able to offer:
CaseMark's approach to AI represents a careful balance between technological advancement and ethical considerations. By removing certain AI safety filters for specific legal use cases, CaseMark enables legal professionals to access the information they need while still maintaining strict controls on who can use the system. This targeted approach ensures that sensitive content is handled responsibly and only by those with the appropriate clearance and need.
Legal professionals should always review case material. CaseMark helps reduce the burden of repeated manual review, enabling legal professionals to put their focus and energy on the most critical aspects of their cases.
As we continue to navigate the complexities of the digital age, tools like CaseMark demonstrate how AI can be harnessed for good, particularly in litigation. By embracing these ethical AI solutions, legal professionals can work more effectively and ultimately provide better service to their clients and the cause of justice.
The future of litigation support is here, and it's powered by ethical AI.