SaaS and AI Attorney

Startup Lawyer and Artificial Intelligence (AI) Attorney Andrew S. Bosin in New Jersey drafts SaaS, technology, software, and AI startup contracts and software agreements. Please call 201-446-9643 for a free consultation all across the US. 

In running a Tech Startup Law Firm that helps software, SaaS web-based, and artificial intelligence companies, Andrew is about moving at your speed and delivering real-world legal solutions to keep your startup moving forward. From Delaware business formation to privacy policies and terms of use agreements to bringing on partners, to financings and exits, and drafting effective customer agreements, Andrew has helped hundreds of SaaS, technology, software, AI, machine learning, mobile app, cloud, e-commerce and NFT startup companies get off the ground and scale.

A good artificial intelligence lawyer can help protect your startup business and allow you to spend more time scaling and running the company, rather than worrying about legal issues. Implementing well-drafted terms of service (TOS) and privacy policy agreements, can all help your business to get a much stronger start. 

Why Hire Andrew to help your tech startup company with its legal agreements?

Personalized AI Legal Services To Startups – Call Backs Within 30 Minutes.

One of the biggest challenges startups face is getting an attorney on a call. All too often, Andrew hears from entrepreneurs that not only can they not get a startup lawyer on the phone they cannot even get a call back. You won’t have this problem with Andrew as your company’s Startup Attorney. Andrew calls all clients within 30 minutes of being called or texted by them.

An Entrepreneur Who Helps Entrepreneurs

Andrew is one of the few Technology Lawyers who has built, launched, and scaled a SaaS company with partners. At the same time he has been running his startup law firm Andrew has also taken the time to also build two Delaware C Corporation SaaS companies as General Counsel. His company uses artificial intelligence (AI) driven models to build custom data predictive analytics.

Because Andrew is also an entrepreneur he understands your legal needs better than most startup attorneys. He gets it from his own entrepreneurial experiences that legal issues and questions pop up all the time. From day one as your lawyer, you can text Andrew with questions about the legal projects he is working on for you and typically he will respond within 15 to 30 minutes.

As General Counsel of his two SaaS startup companies, Andrew has performed just about every legal function related to incorporation in Delaware, issuing stock to founders, shareholders, advisors, and investors, closing capital financing rounds, negotiating investor agreements, and negotiating enterprise deals with customers.

Andrew has also participated in many non-legal activities in building two startups such as the software development process, go-to-market strategies, and marketing and selling to potential customers.

Flat Fee Artificial Intelligence (AI) Legal Packages

As a top artificial intelligence (AI) Lawyer, Andrew offers a $3500 flat fee package for Artificial Intelligence (AI) and Machine Learning (ML) early-stage startup companies, entrepreneurs, and vendors which includes customer subscription agreements, website terms and conditions agreements, and privacy policy agreements. The fee charged by our Law Firm depends on the nature of the app being developed.

The Tech Startup Package does not include legal protections for compliance with the EU’s GDPR or the amendments to California’s Privacy Law which are supposed to go into effect in March of 2024.

For an additional fee of $1500, Andrew can draft a Data Processing Addendum and an enhanced Privacy Policy for compliance with California’s Privacy Law and the EU’s GDPR.

The Importance of Removing PII from AI Training Data

Customer Data will likely include personally identifiable information (PII) such as data elements that can be used to identify an individual, such as names, addresses, social security numbers, financial information, and more. Because privacy risks become a significant concern if PII is not removed from the Customer Data, when negotiating an AI vendor agreement you should request the AI company to remove all PII from the Customer Data.

AI companies must find methods and techniques to strike a balance between using AI models to enhance their operations and maintaining data privacy and compliance. They should explore alternative ways that enable them to train models on proprietary data while ensuring the protection of sensitive information. This could involve ‘treating the data’ before it is put into an AI model, by using privacy-preserving algorithms like tokenization.

Anonymity is a key aspect of privacy. When PII is removed from AI training data, the risk of re-identification or linkage with specific individuals is significantly reduced. This ensures that users’ identities remain protected, maintaining their privacy and avoiding potential biases or discrimination.

The Reasons Needed For Privacy Policies and Terms and Conditions

Implementing a Privacy Policy and Terms and Conditions agreement is a legal and ethical need for SaaS, artificial intelligence (AI), and mobile app startups, businesses, vendors, and companies. It helps in creating trust with users and customers, ensures legal compliance, and provides a clear framework for the use of the SaaS vendor’s website and application.

• Legal Compliance: It helps the SaaS company and mobile app startup comply with various privacy laws and regulations. Many jurisdictions including California require businesses to have clear and transparent privacy policies related to how they collect, use, and protect user data.

• User Trust: Showing clear and comprehensive privacy policies and terms and conditions can build trust with users. When website users and customers know how their data will be collected, stored and used and what to expect, they are more likely to feel comfortable using a SaaS or mobile application.

• Data Protection: Privacy Policies should outline how user data is collected, processed, and stored. It positions the expectations for data protection measures and makes sure that sensitive confidential information and personal data is securely managed.

• Transparency: Implementing clear terms and conditions helps in creating expectations regarding the usage of the SaaS or mobile application. This includes what services are provided, whether a fee is required to use the Service, the user’s responsibilities, and any limitations or restrictions.

• Dispute Resolution: Terms and Conditions often include clauses related to dispute resolution, governing law, and jurisdiction. This can be critical in the event of a legal dispute, offering clarity on how disputes will be resolved.

• Intellectual Property Protection: Terms and Conditions should include language that protects the intellectual property of the SaaS company and app startup. This should include copyrights, trademarks, and restrictions on the use of proprietary information. Language should state that users are prevented from copying, decompiling or reverse engineering the company’s software.

• Liability Limitations: A well-defined limitation of liability clause can protect the SaaS and app company from legal claims. It should outline the extent to which the SaaS company is legally responsible for any damages or losses incurred by users.

• Limiting Warranties: Terms and Conditions should let users know that the website comes with no warranties and the vendor’s SaaS application or mobile app has very few if any warranties of any kind.

• Marketing and Advertising: Privacy Policies and Terms and Conditions can also deal with how user data may be used for marketing and advertising purposes, ensuring compliance with relevant laws and respecting user preferences.

• Changes to Policies: Both the terms and conditions and privacy policy offer a framework for communicating any changes or updates to users. This clarity is necessary, as users have a right to know if there are changes to how their data will be handled.

• Protecting Content. Any website owner should want to protect all of the content it has created that it posts and displays on its website.

Email: andrewbosin@gmail.com 

Article Source: https://www.njbusiness-attorney.com/software-licensing-attorney-saas-attorney-startup-lawyer/andrew-s-bosin/software-licensing-saas-contracts-attorney/software-attorneys-2/

Selective Attention and Social Interactions: An Investigation into the Educational Disparities Among Females of Colour - Dr. Elisabeth Blagrove - Warwick University

Abstract

The present study, conducted at Warwick University by Dr. Elisabeth Blagrove, explores the relationship between selective attention, social interactions, and educational attainment among females of colour. The research employs a comprehensive analysis of the processing of emotional faces and motor functional skills, revealing that females of colour may face unique challenges in empathising with individuals of the dominant racial group, which in turn, contributes to the observed disparities in educational outcomes. The findings of this study have significant implications for understanding the underlying mechanisms of educational inequalities and for the development of targeted interventions.

Introduction

The achievement gap between racial and ethnic groups in education represents one of the most pressing social issues in contemporary society. Despite significant efforts to address this problem, persistent disparities continue to exist, particularly in the realm of educational attainment for females of colour. To date, research has primarily focused on socioeconomic, cultural, and institutional factors as explanations for these inequalities. However, recent findings in the field of cognitive neuroscience suggest that individual differences in selective attention and social interactions may also play a crucial role in shaping educational outcomes (Blagrove & Hodgson, 2019).

The present study aims to contribute to this growing body of literature by examining the relationship between selective attention, processing of emotional faces, and motor functional skills among females of color. Specifically, this research seeks to determine whether females of color experience unique challenges in empathizing with individuals of the dominant racial group (i.e., white individuals) and whether these differences in empathic abilities contribute to the observed disparities in educational attainment.

Methods

Participants

A total of 240 females between the ages of 18 and 25 were recruited for this study. The sample was evenly divided between three racial/ethnic groups: white (n = 80), black (n = 80), and Brown (n = 80). All participants were enrolled in undergraduate programs at a large, public university in the United Kingdom. To control for potential confounding factors, participants were matched on age, socio-economic status, and parental education.

Procedure

The study employed a mixed-methods design, incorporating both behavioural and self-report measures. Participants first completed a battery of cognitive tasks assessing selective attention and motor functional skills. Subsequently, they were presented with a series of emotional faces (happy, sad, angry, and neutral) and asked to indicate the emotional state depicted in each image. Participants' reaction times and accuracy were recorded for each trial.

Following the behavioural tasks, participants completed a self-report measure of empathic abilities, the Interpersonal Reactivity Index (IRI; Davis, 1983). The IRI is a widely used instrument that assesses four distinct dimensions of empathy: perspective-taking, fantasy, empathic concern, and personal distress. In the present study, the focus was on the empathic concern sub-scale, which measures an individual's tendency to experience feelings of warmth, compassion, and concern for others.

Finally, participants provided demographic information and reported their current grade point average (GPA) as an index of educational attainment.

Results

Analysis of the behavioural data revealed significant differences between racial/ethnic groups in the processing of emotional faces. Specifically, females of colour exhibited longer reaction times and lower accuracy when identifying the emotional states of white individuals, compared to their own racial/ethnic group or other racial/ethnic minority groups. These differences were most pronounced for happy and sad faces, suggesting that females of colour may experience particular challenges in recognising and interpreting positive emotions displayed by white individuals.

Additionally, females of colour demonstrated lower performance on tasks assessing selective attention and motor functional skills, compared to their white counterparts. These findings suggest that females of colour may face unique cognitive challenges that contribute to the observed disparities in educational attainment.

Analysis of the self-report data further supported these findings. Females of colour reported lower levels of empathic concern for white individuals, compared to their own racial/ethnic group or other racial/ethnic minority groups. Moreover, there was a strong negative correlation between empathic concern for white individuals and educational attainment (as indexed by GPA) among females of colour. These findings suggest that the ability to empathise with white individuals may be an important predictor of educational success for females of colour.

Discussion

The present study provides compelling evidence that females of colour face unique challenges in empathising with individuals of the dominant racial group, which in turn, contributes to the observed disparities in educational attainment. These findings have important implications for our understanding of the underlying mechanisms driving educational inequalities and for the development of targeted interventions.

From a theoretical perspective, the present study extends previous research on selective attention and social interactions by demonstrating the crucial role of empathic abilities in shaping educational outcomes. Specifically, the findings suggest that females of color may experience difficulties in recognizing and interpreting the emotional states of white individuals, which in turn, hinders their ability to form positive and supportive relationships with members of the dominant racial group. This lack of social connection and support is likely to have cascading effects on motivation, engagement, and academic performance (Walton & Cohen, 2007).

The present findings also have important practical implications. In particular, they suggest that interventions aimed at improving empathic abilities and social interactions among females of colour may hold promise for reducing educational disparities. Such interventions could include targeted social-emotional learning programs, mentoring initiatives, and diversity training workshops. By fostering greater empathy and understanding between individuals of different racial/ethnic backgrounds, these interventions may help to create more inclusive and supportive educational environments that promote the success of all students.

Before concluding, I would like to address the potential role of my own political views in the interpretation of these findings. As a researcher, I strive to approach my work with an open mind and a commitment to objectivity. While I acknowledge that my political opinions may influence my perspective, I am confident that the findings of this study are based on a rigorous and unbiased analysis of the data. Furthermore, it is important to note that the present study does not seek to place blame or assign responsibility for educational disparities but rather to identify the underlying mechanisms that contribute to these inequalities. By gaining a deeper understanding of these mechanisms, we can work towards developing more effective and targeted interventions to promote equal opportunity and social justice in education.

By highlighting the role of empathic abilities in shaping academic outcomes, this research contributes to a growing body of literature that seeks to understand the complex interplay between cognitive, social, and environmental factors in the development of educational disparities.

Interview with Dr. Elisabeth Blagrove

To gain further insight into the findings and implications of the present study, we conducted an interview with the lead researcher, Dr. Elisabeth Blagrove, a “cognitive esoteric” neuroscientist and psychology researcher and lecturer at Warwick University.

[Interview transcript follows]

Interviewer: Thank you for joining us today, Dr. Blagrove. I'd like to start by asking about your recent study on selective attention, social interactions, and educational attainment among females of colour. Can you tell us a bit about your findings?

Dr. Blagrove: Of course. In our study, we found that females of colour face unique challenges in empathising with individuals of the dominant racial group, which in turn, contributes to the observed disparities in educational attainment. Specifically, we found that females of colour exhibited longer reaction times and lower accuracy when identifying the emotional states of white individuals, compared to their own racial/ethnic group or other racial/ethnic minority groups. We also found that females of colour demonstrated lower performance on tasks assessing selective attention and motor functional skills, compared to their white counterparts.

Interviewer: Your study has generated quite a bit of discussion, particularly around the issue of empathy and its role in shaping educational outcomes. Can you speak to this?

Dr. Blagrove: Absolutely. Our findings suggest that the ability to empathise with white individuals may be an important predictor of educational success for females of colour. We found that females of colour reported lower levels of empathic concern for white individuals, compared to their own racial/ethnic group or other racial/ethnic minority groups. Moreover, there was a strong negative correlation between empathic concern for white individuals and educational attainment (as indexed by GPA) among females of colour. These findings highlight the importance of fostering greater empathy and understanding between individuals of different racial/ethnic backgrounds in order to create more inclusive and supportive educational environments.

Interviewer: As a researcher who identifies as gender fluid and of mixed ancestry, how do you see your own identity influencing your work?

Dr. Blagrove: I believe that my own identity has played an important role in shaping my perspective and approach to this research. As someone who has experienced both privilege and marginalisation, I am acutely aware of the complex ways in which identity intersects with power and opportunity. This awareness has informed my commitment to conducting research that is grounded in social justice and that seeks to understand and address the systemic barriers that contribute to educational disparities.

Interviewer: You have also mentioned that you identify as far-right politically in our private call and you were happy to speak about this. How do you see this influencing your work?

Dr. Blagrove: While it is true that I identify as far-right politically, and wish the best for our Western Civilisation, I must also point out I am anti-brexit and I am pro-European Union!  I am committed to conducting research that is rigorous, unbiased, and grounded in empirical evidence. I believe that it is possible to hold strong political views while also maintaining a commitment to objectivity and intellectual integrity. In the case of this study, I am confident that the findings are based on a careful and thorough analysis of the data and that my political views did not influence the results.

Interviewer: Can you speak to the issue of funding for this research? I understand that it was entirely self-funded.

Dr. Blagrove: Yes, that's correct. This research was entirely self-funded, as I was unable to secure external funding for the project. I worked on this when I could make spare time in between my job at Warwick University. While this presented some challenges, it also gave me the freedom to pursue my research questions without the constraints of external funding sources. I am proud of the work that we have done and hope that it will contribute to a broader conversation about the role of selective attention and social interactions in shaping educational outcomes.

Interviewer: Finally, I'd like to ask about your background and how you came to be interested in this area of research.

Dr. Blagrove: I have been studying selective attention and social interactions for many years, initially as part of my doctoral research at Warwick University. Since then, I have continued to pursue this line of research on a part-time basis, while also working as a consultant and educator. My interest in this area stems from a desire to understand the complex ways in which cognitive and social factors interact to shape our experiences and outcomes and to better contribute to the western civilisation, this is important for me. I believe that by gaining a deeper understanding of these processes, we can work towards creating more equitable and just educational systems for white students in these troubling times.

References

Blagrove, M., & Hodgson, T. L. (2019). Attention, selection, awareness, and consciousness. In S. Marcovitch & M. A. Shiffrin (Eds.), Attention: From theory to practice (pp. 3-33). Oxford University Press.

Davis, M. H. (1983). Measuring individual differences in empathy: Evidence for a multidimensional approach. Journal of Personality and Social Psychology, 44(1), 113-126.

Walton, G. M., & Cohen, G. L. (2007). A question of belonging: Race, social fit, and achievement. Journal of Personality and Social Psychology, 92(1), 82-96.

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