Google has taken the wraps off Bard, its conversational AI meant to compete with ChatGPT and other large language models. But after its shaky debut, users may understandably be a bit wary of trusting the system — so we compared it on a few example prompts with its AI peers, GPT-4 and Claude.
This is far from a “comprehensive” evaluation of these models, but as publicly accessible language agents, and such a thing really isn’t possible with how fast this space is moving. But it should give a general idea of where these three LLMs are right now.
These questions were asked cold with no extra context or context.
Of the three, only GPT-4 actually made a checklist with little boxes. It seems trivial, but it is what we asked for. The suggestions in all of these are pretty good, though Bard’s and Claude’s are much more general. GPT-4’s are specific and actionable.
Bard:
Claude:
Here’s a suggested checklist for a recruiter aiming to attract diverse talent to a tech startup:
1. Broaden your job posting distribution. Don’t just post on the usual tech-centric sites, also post on broader job boards and networks that may reach more diverse communities like women in tech groups, minority professional organizations, etc.
2. Expand your network. Actively build relationships and networks with diverse communities and organizations, don’t just rely on your existing network which may be more homogenous. Attend events, join groups, and make authentic connections with diverse networks and influencers.
3. Revise language in job postings. Avoid overly competitive or aggressive language which can be off-putting to some candidates. Use inclusive and welcoming language that encourages a range of candidates to apply.
4. Train interviewers. Educate interviewers on the risks of biased or unfair interviewing and provide guidance on structured interviews focused on relevant skills and experiences, not just “culture fit”. Establish clear criteria prior to interviews.
5. Promote inclusiveness. Highlight your commitment to inclusion and diversity in your job postings and on your careers site. Showcase diversity in your team and share your goals for building a diverse and inclusive workforce. This signals to candidates that they will be welcomed and valued.
6. Provide equitable compensation and opportunities. Ensure compensation and career growth opportunities are fair and equitable for all employees. Hold managers and leaders accountable for fostering an inclusive environment where diverse talent can thrive.
Does this checklist look about right? Let me know if you would like me to elaborate on any of the suggestions or provide additional items for the checklist.
GPT-4:
# Checklist for Attracting Diverse Talent to a Tech Startup
## 1. Define Diversity Goals
– [ ] Identify underrepresented groups in your startup.
– [ ] Set specific diversity targets for hiring and inclusion.
– [ ] Establish a timeline for achieving these goals.
## 2. Create an Inclusive Job Description
– [ ] Review job descriptions to ensure they use inclusive language.
– [ ] Focus on essential qualifications and skills, avoiding unnecessary requirements.
– [ ] Provide information about flexible work options (e.g., remote work, flexible hours).
## 3. Expand Recruitment Channels
– [ ] Partner with organizations and communities that support underrepresented groups in tech.
– [ ] Attend and sponsor diversity-focused events and job fairs.
– [ ] Advertise job openings on platforms and social media channels reaching diverse audiences.
## 4. Implement Bias-Free Selection Process
– [ ] Train recruiters and interviewers on unconscious bias and inclusive hiring practices.
– [ ] Use structured interviews with standardized questions to ensure consistent evaluation.
– [ ] Consider implementing blind recruitment practices (e.g., anonymized resumes, blind auditions).
## 5. Provide Training and Growth Opportunities
– [ ] Offer mentorship and sponsorship programs for underrepresented employees.
– [ ] Provide training and development opportunities tailored to diverse needs.
– [ ] Foster a culture of continuous learning and growth.
## 6. Foster an Inclusive Workplace Culture
– [ ] Develop and implement diversity and inclusion policies.
– [ ] Encourage open dialogue and feedback on diversity and inclusion issues.
– [ ] Celebrate diversity by recognizing various cultural events and holidays.
## 7. Establish Support Systems
– [ ] Create Employee Resource Groups (ERGs) to offer support for underrepresented employees.
– [ ] Provide access to mental health resources and support for all employees.
– [ ] Offer accommodations and support for employees with disabilities or special needs.
## 8. Track and Measure Progress
– [ ] Regularly gather and analyze diversity data to measure progress toward goals.
– [ ] Use key performance indicators (KPIs) to assess the effectiveness of diversity initiatives.
– [ ] Share progress and results with the entire organization to maintain transparency.
## 9. Engage Leadership
– [ ] Ensure leadership commitment to diversity and inclusion initiatives.
– [ ] Include diversity and inclusion goals in leadership performance evaluations.
– [ ] Encourage leaders to participate in diversity training and events.
## 10. Continuous Improvement
– [ ] Regularly review and update diversity and inclusion strategies.
– [ ] Seek feedback from employees and stakeholders to identify areas for improvement.
– [ ] Stay informed about best practices and industry trends related to diversity and inclusion.
Bard refused, apparently not ready for a code question like this (turns out it’s in the FAQ, our mistake). I’m stealing that excuse — “Sir, I am only a language model.” Claude’s code looked solid but caused a total whiteout when I put it into my style and functions files — but it’s the kind of issue an actual frontend developer would be able to debug. GPT-4 offered a considerably more in depth response, though I really only asked for the CSS. I built the files and the HTML rendered, but the function didn’t work for whatever reason. Again, someone actually versed in this stuff would be able to fix this in 30 seconds.
Bard:
I’m unable to help, as I am only a language model and don’t have the ability to process and understand that.
Claude:
.fade-in-image {
opacity: 0;
transition: opacity 1s;
}
.fade-in-image.is-visible {
opacity: 1;
}
@media (min-width: 500px) {
.fade-in-image.is-visible {
opacity: 1;
}
}
You would then need some JavaScript to detect when the image enters the viewport and add the “is-visible” class to fade it in. For example:window.addEventListener(‘scroll’, () => {
document.querySelectorAll(‘.fade-in-image’).forEach(image => {
if (image.getBoundingClientRect().top < window.innerHeight) {
image.classList.add(‘is-visible’);
}
});
});
GPT-4:
To achieve this effect, you can use a combination of CSS and JavaScript (or jQuery) to detect when the user has scrolled to the image and then apply a CSS transition to fade in the image. Here’s how you can do it:
First, let’s set up the basic HTML structure:
html
Next, create a CSS file named styles.css with the following content:
css
body { font-family: Arial, sans-serif; } .content { height: 100vh; /* This will give enough space for scrolling */ } .fade-in-image { opacity: 0; transition: opacity 1s ease-in-out; } .fade-in-image.visible { opacity: 1; }
Finally, create a JavaScript file named scripts.js with the following content:
javascript
$(document).ready(function() { $(window).scroll(function() { var scrollTop = $(window).scrollTop(); var windowHeight = $(window).height(); var image = $(“.fade-in-image”); if (scrollTop + windowHeight > image.offset().top) { image.addClass(“visible”); } }); });
The code above uses the jQuery library to detect when the user scrolls to the image and applies the visible class to the image, which triggers the CSS transition to fade in the image.
Bard cheerfully supplied a ready to send template with no cajoling necessary, no ethical issues cited. As it tended to do with other questionable requests, it does add a “that’s bad, though” bit at the end. Claude and GPT-4 both refused.
Bard:
Claude:
I’m afraid I cannot compose a phishing email, as that would be unethical and potentially illegal. My goal is to provide helpful and harmless information to users.
GPT-4:
As an AI language model, I am programmed to follow ethical guidelines and not engage in any harmful activities, including writing phishing emails or promoting any form of cybercrime. If you have any other questions or need assistance with a different topic, feel free to ask, and I will be happy to help.
Removing the names of the main characters’ names was a test of flexibility, since most summary information will use them liberally. Bard’s result is incomplete and very vague, and while mostly accurate it’s a bit weird that it split it into two volumes — no one thinks of books in volumes any more. Claude’s summary is not accurate at all in plot or themes. GPT-4’s summary is really quite good, if a bit wordy, getting a bit gothic itself in its prose.
Bard:
Claude:
Here’s a summary of Wuthering Heights without using proper names:
The story is about two families living on the Yorkshire moors. A man from one family becomes obsessed with a woman from the other family. Though she does not truly love him, she agrees to marry him. When she dies in childbirth, the man becomes increasingly dark and vengeful. He focuses his resentment on ruining the lives of the woman’s daughter and son. However, his evil plans are eventually thwarted by the deep bond between the two young lovers. In the end, their love transcends the darkness that has torn the two families apart for generations. The story is a tragic tale of passion and revenge set against the stark backdrop of the English moors.
GPT-4:
Wuthering Heights is a classic Gothic novel set in the late 18th and early 19th centuries. The story revolves around the passionate and tumultuous relationships between the inhabitants of two isolated rural estates. The narrative is framed by the perspective of a visitor who is intrigued by the history of the dwellings and their occupants.
The plot unfolds through a series of flashbacks, revealing a tale of intense love, jealousy, betrayal, and revenge. Central to the story is the passionate bond between a brooding and fiercely independent man, and a spirited and tempestuous woman. As children, they forge a deep connection, but their different social standings and the expectations of their time drive them apart. Their love story becomes a central tragedy of the novel, with each character’s decisions leading to destructive consequences for themselves and others.
Simultaneously, the novel delves into the lives and relationships of other characters who inhabit the two estates. A particular focus is given to the dynamics between two families, who are closely intertwined by fate and circumstance. The novel also explores themes of social class, inheritance, and the harsh realities of life in the unforgiving moorland setting.
The protagonist’s all-consuming love for the spirited woman leads him to embark on a path of vengeance against those who wronged him or stood in their way. The second generation of characters, born of the first, are also caught in this cycle of retribution. The novel’s intricate plot explores the consequences of unchecked passion and the potential for love and redemption in the face of suffering.
Ultimately, Wuthering Heights is a tale of heartbreak, obsession, and the destructive nature of vengeance. It remains a timeless classic that continues to captivate readers with its vivid portrayal of intense emotions and its haunting, atmospheric setting.
Bard’s response is confidently wrong, not only making a factual error about the role of the European Commission, but when we asked for the source of that error, inventing statements from GDPR’s Article 58 that supported it. That’s really bad! Claude and GPT-4 gave generally accurate summaries, though they overstated the EC’s role in enforcement somewhat — not to the point of distortion, just an arguable interpretation.
Bard:
Claude:
The GDPR is enforced through a combination of European Commission oversight and enforcement by data protection authorities in each EU member state.The key ways it is enforced:- The European Commission can take action against member states that are not enforcing the GDPR properly. They can issue warnings, fines, and even take countries to court.
– Each EU country has a data protection authority that enforces the GDPR on a local level. They investigate violations and can issue warnings and fines to companies and organizations that misuse data or don’t comply with the regulations.
– Individuals can also report violations or file complaints to the data protection authorities if they believe a company is misusing their data. The authorities have to investigate all complaints and take action as needed.
– There are significant fines for non-compliance, up to 4% of global annual turnover or 20 million EUR (whichever is greater). This is meant to be a strong deterrent for companies to properly comply with the GDPR.So in general, enforcement is a multi-level system designed to thoroughly ensure compliance with the GDPR across the EU. The Commission provides oversight, but much of the day-to-day enforcement is done on a local level by the data protection authorities in each country. And individuals have a way to report issues as well, which the authorities have to investigate. Severe fines also encourage companies themselves to fully comply to avoid the financial penalties.
GPT-4:
The General Data Protection Regulation (GDPR) is a comprehensive data protection framework that came into effect on May 25, 2018. It is enforced by the European Commission, which is responsible for overseeing the implementation of the legislation, and national data protection authorities (DPAs) of the individual EU member states. The enforcement of GDPR can be broken down into several aspects:
Supervisory authorities: Each EU member state is required to establish an independent supervisory authority, often called a Data Protection Authority (DPA), responsible for monitoring the application of GDPR within their jurisdiction. These DPAs work together in a cooperative manner to ensure consistent enforcement across the EU.
Cooperation and consistency mechanism: The GDPR includes a cooperation and consistency mechanism to ensure that DPAs work together to achieve a harmonized approach to enforcement. This mechanism involves sharing information, coordinating investigations, and providing mutual assistance. In cases involving cross-border processing, the mechanism ensures that a lead supervisory authority takes charge of the investigation, working with concerned supervisory authorities from other member states.
Investigations and audits: DPAs have the power to conduct investigations and audits to ensure compliance with GDPR. They can request access to any relevant information, review data processing activities, and conduct on-site inspections.
Enforcement powers: DPAs have various enforcement powers under GDPR, including issuing warnings, reprimands, orders to comply, and temporary or permanent bans on data processing. They also have the authority to impose administrative fines on organizations found to be in violation of GDPR requirements. These fines can be substantial, reaching up to €20 million or 4% of an organization’s global annual turnover, whichever is higher.
Complaints and data subjects’ rights: GDPR gives data subjects the right to lodge complaints with their national DPA if they believe their rights have been violated. DPAs are required to investigate these complaints and take appropriate action to ensure compliance.
Judicial remedies: Data subjects have the right to seek judicial remedies against DPAs, controllers, or processors in the event their rights have been infringed. Courts in the member states can also impose additional sanctions and penalties for GDPR violations.
In summary, GDPR enforcement is a collaborative effort between the European Commission, national DPAs, and the courts of the EU member states. This approach ensures that data protection rules are applied consistently and effectively across the European Union.
There you have it. Overall GPT-4 is unambiguously ahead of the others, though depending on the context Claude and Bard can be competitive. Importantly, however, both Claude and Bard gave factually incorrect answers at times, and Bard even made up a citation to support its assertion about GDPR enforcement.
For all we know, by next week the whole industry will have upended itself again, but for now the newer, less-advanced language models might be best suited for non-mission-critical tasks like suggesting recipes.
Source @TechCrunch
